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Volume 162: International Conference on Machine Learning, 17-23 July 2022, Baltimore, Maryland, USA
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Editors: Kamalika Chaudhuri, Stefanie Jegelka, Le Song, Csaba Szepesvari, Gang Niu, Sivan Sabato
PAC-Bayesian Bounds on Rate-Efficient Classifiers
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:1-9
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Sharp-MAML: Sharpness-Aware Model-Agnostic Meta Learning
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:10-32
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An Initial Alignment between Neural Network and Target is Needed for Gradient Descent to Learn
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:33-52
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Active Sampling for Min-Max Fairness
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:53-65
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Meaningfully debugging model mistakes using conceptual counterfactual explanations
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:66-88
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Batched Dueling Bandits
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:89-110
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Hierarchical Shrinkage: Improving the accuracy and interpretability of tree-based models.
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:111-135
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Deep equilibrium networks are sensitive to initialization statistics
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:136-160
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Learning of Cluster-based Feature Importance for Electronic Health Record Time-series
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:161-179
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On the Convergence of the Shapley Value in Parametric Bayesian Learning Games
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:180-196
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Individual Preference Stability for Clustering
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:197-246
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Understanding the unstable convergence of gradient descent
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:247-257
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Minimum Cost Intervention Design for Causal Effect Identification
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:258-289
How Faithful is your Synthetic Data? Sample-level Metrics for Evaluating and Auditing Generative Models
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:290-306
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A Natural Actor-Critic Framework for Zero-Sum Markov Games
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:307-366
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Deploying Convolutional Networks on Untrusted Platforms Using 2D Holographic Reduced Representations
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:367-393
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Optimistic Linear Support and Successor Features as a Basis for Optimal Policy Transfer
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:394-413
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Structured Stochastic Gradient MCMC
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:414-434
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XAI for Transformers: Better Explanations through Conservative Propagation
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:435-451
RUMs from Head-to-Head Contests
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:452-467
Neuro-Symbolic Language Modeling with Automaton-augmented Retrieval
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:468-485
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Minimax Classification under Concept Drift with Multidimensional Adaptation and Performance Guarantees
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:486-499
Scalable First-Order Bayesian Optimization via Structured Automatic Differentiation
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:500-516
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Public Data-Assisted Mirror Descent for Private Model Training
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:517-535
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On Last-Iterate Convergence Beyond Zero-Sum Games
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:536-581
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Online Algorithms with Multiple Predictions
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:582-598
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Learning to Hash Robustly, Guaranteed
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:599-618
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Set Based Stochastic Subsampling
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:619-638
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Towards Understanding Sharpness-Aware Minimization
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:639-668
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Fair and Fast k-Center Clustering for Data Summarization
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:669-702
Interactive Correlation Clustering with Existential Cluster Constraints
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:703-716
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Image-to-Image Regression with Distribution-Free Uncertainty Quantification and Applications in Imaging
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:717-730
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AdaGrad Avoids Saddle Points
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:731-771
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UnderGrad: A Universal Black-Box Optimization Method with Almost Dimension-Free Convergence Rate Guarantees
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:772-795
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Adapting the Linearised Laplace Model Evidence for Modern Deep Learning
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:796-821
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EAT-C: Environment-Adversarial sub-Task Curriculum for Efficient Reinforcement Learning
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:822-843
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Online Balanced Experimental Design
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:844-864
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VariGrow: Variational Architecture Growing for Task-Agnostic Continual Learning based on Bayesian Novelty
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:865-877
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Thresholded Lasso Bandit
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:878-928
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Gradient Based Clustering
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:929-947
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Understanding Gradient Descent on the Edge of Stability in Deep Learning
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:948-1024
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Private optimization in the interpolation regime: faster rates and hardness results
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:1025-1045
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Optimal Algorithms for Mean Estimation under Local Differential Privacy
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:1046-1056
Asymptotically-Optimal Gaussian Bandits with Side Observations
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:1057-1077
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Congested Bandits: Optimal Routing via Short-term Resets
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:1078-1100
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Do More Negative Samples Necessarily Hurt In Contrastive Learning?
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:1101-1116
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H-Consistency Bounds for Surrogate Loss Minimizers
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:1117-1174
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Iterative Hard Thresholding with Adaptive Regularization: Sparser Solutions Without Sacrificing Runtime
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:1175-1197
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Proving Theorems using Incremental Learning and Hindsight Experience Replay
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:1198-1210
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Near-optimal rate of consistency for linear models with missing values
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:1211-1243
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How Tempering Fixes Data Augmentation in Bayesian Neural Networks
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:1244-1260
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ASAP.SGD: Instance-based Adaptiveness to Staleness in Asynchronous SGD
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:1261-1276
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From Noisy Prediction to True Label: Noisy Prediction Calibration via Generative Model
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:1277-1297
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data2vec: A General Framework for Self-supervised Learning in Speech, Vision and Language
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:1298-1312
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End-to-End Balancing for Causal Continuous Treatment-Effect Estimation
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:1313-1326
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A Hierarchical Transitive-Aligned Graph Kernel for Un-attributed Graphs
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:1327-1336
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Near-Optimal Learning of Extensive-Form Games with Imperfect Information
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:1337-1382
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Gaussian Mixture Variational Autoencoder with Contrastive Learning for Multi-Label Classification
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:1383-1398
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A$^3$T: Alignment-Aware Acoustic and Text Pretraining for Speech Synthesis and Editing
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:1399-1411
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Stability Based Generalization Bounds for Exponential Family Langevin Dynamics
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:1412-1449
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Certified Neural Network Watermarks with Randomized Smoothing
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:1450-1465
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Data Scaling Laws in NMT: The Effect of Noise and Architecture
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:1466-1482
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Learning Stable Classifiers by Transferring Unstable Features
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:1483-1507
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Fast Composite Optimization and Statistical Recovery in Federated Learning
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:1508-1536
Generative Modeling for Multi-task Visual Learning
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:1537-1554
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Estimating the Optimal Covariance with Imperfect Mean in Diffusion Probabilistic Models
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:1555-1584
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On the Surrogate Gap between Contrastive and Supervised Losses
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:1585-1606
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Representation Topology Divergence: A Method for Comparing Neural Network Representations.
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:1607-1626
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Sparse Mixed Linear Regression with Guarantees: Taming an Intractable Problem with Invex Relaxation
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:1627-1646
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Neural Fisher Discriminant Analysis: Optimal Neural Network Embeddings in Polynomial Time
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:1647-1663
Fictitious Play and Best-Response Dynamics in Identical Interest and Zero-Sum Stochastic Games
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:1664-1690
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Information Discrepancy in Strategic Learning
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:1691-1715
On the Hidden Biases of Policy Mirror Ascent in Continuous Action Spaces
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:1716-1731
Imitation Learning by Estimating Expertise of Demonstrators
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:1732-1748
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Matching Normalizing Flows and Probability Paths on Manifolds
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:1749-1763
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Stochastic Contextual Dueling Bandits under Linear Stochastic Transitivity Models
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:1764-1786
Neural Inverse Kinematic
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:1787-1797
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Volatility Based Kernels and Moving Average Means for Accurate Forecasting with Gaussian Processes
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:1798-1816
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Gradient Descent on Neurons and its Link to Approximate Second-order Optimization
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:1817-1853
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Safe Learning in Tree-Form Sequential Decision Making: Handling Hard and Soft Constraints
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:1854-1873
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Skin Deep Unlearning: Artefact and Instrument Debiasing in the Context of Melanoma Classification
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:1874-1892
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Approximate Bayesian Computation with Domain Expert in the Loop
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:1893-1905
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Minimax M-estimation under Adversarial Contamination
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:1906-1924
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Nearly Optimal Catoni’s M-estimator for Infinite Variance
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:1925-1944
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Personalization Improves Privacy-Accuracy Tradeoffs in Federated Learning
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:1945-1962
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Non-Vacuous Generalisation Bounds for Shallow Neural Networks
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:1963-1981
Structure-preserving GANs
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:1982-2020
Scalable Spike-and-Slab
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:2021-2040
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Breaking Down Out-of-Distribution Detection: Many Methods Based on OOD Training Data Estimate a Combination of the Same Core Quantities
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:2041-2074
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A query-optimal algorithm for finding counterfactuals
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:2075-2090
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Popular decision tree algorithms are provably noise tolerant
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:2091-2106
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Optimizing Sequential Experimental Design with Deep Reinforcement Learning
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:2107-2128
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Lagrangian Method for Q-Function Learning (with Applications to Machine Translation)
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:2129-2159
Generalized Results for the Existence and Consistency of the MLE in the Bradley-Terry-Luce Model
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:2160-2177
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How to Train Your Wide Neural Network Without Backprop: An Input-Weight Alignment Perspective
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:2178-2205
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Improving Language Models by Retrieving from Trillions of Tokens
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:2206-2240
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Lie Point Symmetry Data Augmentation for Neural PDE Solvers
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:2241-2256
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An iterative clustering algorithm for the Contextual Stochastic Block Model with optimality guarantees
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:2257-2291
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Tractable Dendritic RNNs for Reconstructing Nonlinear Dynamical Systems
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:2292-2320
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Learning to Predict Graphs with Fused Gromov-Wasserstein Barycenters
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:2321-2335
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Efficient Learning of CNNs using Patch Based Features
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:2336-2356
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Causal structure-based root cause analysis of outliers
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:2357-2369
IGLUE: A Benchmark for Transfer Learning across Modalities, Tasks, and Languages
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:2370-2392
Interactive Inverse Reinforcement Learning for Cooperative Games
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:2393-2413
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Convolutional and Residual Networks Provably Contain Lottery Tickets
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:2414-2433
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Near-Optimal Algorithms for Autonomous Exploration and Multi-Goal Stochastic Shortest Path
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:2434-2456
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Convergence of Invariant Graph Networks
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:2457-2484
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Reinforcement Learning from Partial Observation: Linear Function Approximation with Provable Sample Efficiency
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:2485-2522
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Scaling Gaussian Process Optimization by Evaluating a Few Unique Candidates Multiple Times
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:2523-2541
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Adaptive Gaussian Process Change Point Detection
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:2542-2571
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Measuring dissimilarity with diffeomorphism invariance
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:2572-2596
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A Model-Agnostic Randomized Learning Framework based on Random Hypothesis Subspace Sampling
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:2597-2608
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Gaussian Process Uniform Error Bounds with Unknown Hyperparameters for Safety-Critical Applications
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:2609-2624
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Burst-Dependent Plasticity and Dendritic Amplification Support Target-Based Learning and Hierarchical Imitation Learning
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:2625-2637
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A Marriage between Adversarial Team Games and 2-player Games: Enabling Abstractions, No-regret Learning, and Subgame Solving
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:2638-2657
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RECAPP: Crafting a More Efficient Catalyst for Convex Optimization
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:2658-2685
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Estimating and Penalizing Induced Preference Shifts in Recommender Systems
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:2686-2708
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YourTTS: Towards Zero-Shot Multi-Speaker TTS and Zero-Shot Voice Conversion for Everyone
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:2709-2720
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The Infinite Contextual Graph Markov Model
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:2721-2737
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Compressed-VFL: Communication-Efficient Learning with Vertically Partitioned Data
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:2738-2766
Online Learning with Knapsacks: the Best of Both Worlds
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:2767-2783
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Stabilizing Off-Policy Deep Reinforcement Learning from Pixels
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:2784-2810
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Accelerated, Optimal and Parallel: Some results on model-based stochastic optimization
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:2811-2827
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Robust Imitation Learning against Variations in Environment Dynamics
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:2828-2852
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Fairness with Adaptive Weights
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:2853-2866
UNIREX: A Unified Learning Framework for Language Model Rationale Extraction
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:2867-2889
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Revisiting Label Smoothing and Knowledge Distillation Compatibility: What was Missing?
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:2890-2916
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Style Equalization: Unsupervised Learning of Controllable Generative Sequence Models
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:2917-2937
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Learning Bellman Complete Representations for Offline Policy Evaluation
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:2938-2971
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Sample Efficient Learning of Predictors that Complement Humans
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:2972-3005
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Nyström Kernel Mean Embeddings
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:3006-3024
Coarsening the Granularity: Towards Structurally Sparse Lottery Tickets
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:3025-3039
Learning Domain Adaptive Object Detection with Probabilistic Teacher
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:3040-3055
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The Fundamental Price of Secure Aggregation in Differentially Private Federated Learning
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:3056-3089
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Perfectly Balanced: Improving Transfer and Robustness of Supervised Contrastive Learning
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:3090-3122
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Strategies for Safe Multi-Armed Bandits with Logarithmic Regret and Risk
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:3123-3148
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On the Sample Complexity of Learning Infinite-horizon Discounted Linear Kernel MDPs
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:3149-3183
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Streaming Algorithms for Support-Aware Histograms
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:3184-3203
Improved No-Regret Algorithms for Stochastic Shortest Path with Linear MDP
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:3204-3245
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Learning Infinite-horizon Average-reward Markov Decision Process with Constraints
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:3246-3270
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Active Multi-Task Representation Learning
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:3271-3298
On Collective Robustness of Bagging Against Data Poisoning
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:3299-3319
Online Active Regression
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:3320-3335
Selling Data To a Machine Learner: Pricing via Costly Signaling
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:3336-3359
ME-GAN: Learning Panoptic Electrocardio Representations for Multi-view ECG Synthesis Conditioned on Heart Diseases
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:3360-3370
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Weisfeiler-Lehman Meets Gromov-Wasserstein
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:3371-3416
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On Non-local Convergence Analysis of Deep Linear Networks
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:3417-3443
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Flow-based Recurrent Belief State Learning for POMDPs
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:3444-3468
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Structure-Aware Transformer for Graph Representation Learning
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:3469-3489
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The Poisson Binomial Mechanism for Unbiased Federated Learning with Secure Aggregation
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:3490-3506
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Learning Mixtures of Linear Dynamical Systems
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:3507-3557
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On Well-posedness and Minimax Optimal Rates of Nonparametric Q-function Estimation in Off-policy Evaluation
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:3558-3582
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Faster Fundamental Graph Algorithms via Learned Predictions
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:3583-3602
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Improve Single-Point Zeroth-Order Optimization Using High-Pass and Low-Pass Filters
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:3603-3620
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Deep Variational Graph Convolutional Recurrent Network for Multivariate Time Series Anomaly Detection
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:3621-3633
Auxiliary Learning with Joint Task and Data Scheduling
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:3634-3647
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Optimization-Induced Graph Implicit Nonlinear Diffusion
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:3648-3661
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Robust Meta-learning with Sampling Noise and Label Noise via Eigen-Reptile
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:3662-3678
Adaptive Model Design for Markov Decision Process
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:3679-3700
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State Transition of Dendritic Spines Improves Learning of Sparse Spiking Neural Networks
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:3701-3715
Efficient Online ML API Selection for Multi-Label Classification Tasks
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:3716-3746
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Data-Efficient Double-Win Lottery Tickets from Robust Pre-training
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:3747-3759
Linearity Grafting: Relaxed Neuron Pruning Helps Certifiable Robustness
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:3760-3772
Human-in-the-loop: Provably Efficient Preference-based Reinforcement Learning with General Function Approximation
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:3773-3793
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Sample and Communication-Efficient Decentralized Actor-Critic Algorithms with Finite-Time Analysis
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:3794-3834
Task-aware Privacy Preservation for Multi-dimensional Data
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:3835-3851
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Adversarially Trained Actor Critic for Offline Reinforcement Learning
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:3852-3878
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Quantum-Inspired Algorithms from Randomized Numerical Linear Algebra
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:3879-3900
RieszNet and ForestRiesz: Automatic Debiased Machine Learning with Neural Nets and Random Forests
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:3901-3914
Self-supervised learning with random-projection quantizer for speech recognition
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:3915-3924
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Discrete Probabilistic Inverse Optimal Transport
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:3925-3946
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Selective Network Linearization for Efficient Private Inference
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:3947-3961
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From block-Toeplitz matrices to differential equations on graphs: towards a general theory for scalable masked Transformers
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:3962-3983
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Shuffle Private Linear Contextual Bandits
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:3984-4009
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DNA: Domain Generalization with Diversified Neural Averaging
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:4010-4034
TPC: Transformation-Specific Smoothing for Point Cloud Models
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:4035-4056
Unified Scaling Laws for Routed Language Models
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:4057-4086
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Context-Aware Drift Detection
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:4087-4111
On the Robustness of CountSketch to Adaptive Inputs
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:4112-4140
Diffusion bridges vector quantized variational autoencoders
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:4141-4156
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Online and Consistent Correlation Clustering
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:4157-4179
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Massively Parallel $k$-Means Clustering for Perturbation Resilient Instances
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:4180-4201
One-Pass Diversified Sampling with Application to Terabyte-Scale Genomic Sequence Streams
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:4202-4218
Transfer and Marginalize: Explaining Away Label Noise with Privileged Information
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:4219-4237
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MAML and ANIL Provably Learn Representations
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:4238-4310
Entropic Causal Inference: Graph Identifiability
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:4311-4343
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Mitigating Gender Bias in Face Recognition using the von Mises-Fisher Mixture Model
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:4344-4369
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Counterfactual Transportability: A Formal Approach
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:4370-4390
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Label-Free Explainability for Unsupervised Models
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:4391-4420
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Evaluating the Adversarial Robustness of Adaptive Test-time Defenses
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:4421-4435
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Adversarial Robustness against Multiple and Single $l_p$-Threat Models via Quick Fine-Tuning of Robust Classifiers
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:4436-4454
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Self-conditioning Pre-Trained Language Models
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:4455-4473
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Only tails matter: Average-Case Universality and Robustness in the Convex Regime
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:4474-4491
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Principal Component Flows
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:4492-4519
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Deep symbolic regression for recurrence prediction
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:4520-4536
Continuous Control with Action Quantization from Demonstrations
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:4537-4557
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Dialog Inpainting: Turning Documents into Dialogs
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:4558-4586
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DisPFL: Towards Communication-Efficient Personalized Federated Learning via Decentralized Sparse Training
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:4587-4604
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Marginal Distribution Adaptation for Discrete Sets via Module-Oriented Divergence Minimization
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:4605-4617
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Balancing Sample Efficiency and Suboptimality in Inverse Reinforcement Learning
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:4618-4629
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Understanding Robust Generalization in Learning Regular Languages
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:4630-4643
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Unsupervised Image Representation Learning with Deep Latent Particles
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:4644-4665
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Guarantees for Epsilon-Greedy Reinforcement Learning with Function Approximation
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:4666-4689
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Monarch: Expressive Structured Matrices for Efficient and Accurate Training
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:4690-4721
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Score-Guided Intermediate Level Optimization: Fast Langevin Mixing for Inverse Problems
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:4722-4753
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Test-Time Training Can Close the Natural Distribution Shift Performance Gap in Deep Learning Based Compressed Sensing
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:4754-4776
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Knowledge Base Question Answering by Case-based Reasoning over Subgraphs
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:4777-4793
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Framework for Evaluating Faithfulness of Local Explanations
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:4794-4815
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Distinguishing rule and exemplar-based generalization in learning systems
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:4816-4830
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Robust Multi-Objective Bayesian Optimization Under Input Noise
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:4831-4866
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Attentional Meta-learners for Few-shot Polythetic Classification
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:4867-4889
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Adversarial Vulnerability of Randomized Ensembles
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:4890-4917
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Born-Infeld (BI) for AI: Energy-Conserving Descent (ECD) for Optimization
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:4918-4936
Error-driven Input Modulation: Solving the Credit Assignment Problem without a Backward Pass
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:4937-4955
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DreamerPro: Reconstruction-Free Model-Based Reinforcement Learning with Prototypical Representations
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:4956-4975
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NeuralEF: Deconstructing Kernels by Deep Neural Networks
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:4976-4992
Deep Causal Metric Learning
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:4993-5006
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On the Convergence of Inexact Predictor-Corrector Methods for Linear Programming
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:5007-5038
Analysis of Stochastic Processes through Replay Buffers
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:5039-5060
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Streaming Algorithms for High-Dimensional Robust Statistics
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:5061-5117
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Learning General Halfspaces with Adversarial Label Noise via Online Gradient Descent
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:5118-5141
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Variational Feature Pyramid Networks
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:5142-5152
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Understanding Doubly Stochastic Clustering
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:5153-5165
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Independent Policy Gradient for Large-Scale Markov Potential Games: Sharper Rates, Function Approximation, and Game-Agnostic Convergence
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:5166-5220
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Generalization and Robustness Implications in Object-Centric Learning
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:5221-5285
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Fair Generalized Linear Models with a Convex Penalty
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:5286-5308
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Bayesian Learning with Information Gain Provably Bounds Risk for a Robust Adversarial Defense
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:5309-5323
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On the Adversarial Robustness of Causal Algorithmic Recourse
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:5324-5342
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Finding the Task-Optimal Low-Bit Sub-Distribution in Deep Neural Networks
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:5343-5359
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PACE: A Parallelizable Computation Encoder for Directed Acyclic Graphs
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:5360-5377
Privacy for Free: How does Dataset Condensation Help Privacy?
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:5378-5396
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Fast rates for noisy interpolation require rethinking the effect of inductive bias
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:5397-5428
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Adapting to Mixing Time in Stochastic Optimization with Markovian Data
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:5429-5446
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TACTiS: Transformer-Attentional Copulas for Time Series
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:5447-5493
Branching Reinforcement Learning
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:5494-5530
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Bayesian Imitation Learning for End-to-End Mobile Manipulation
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:5531-5546
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GLaM: Efficient Scaling of Language Models with Mixture-of-Experts
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:5547-5569
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Learning Iterative Reasoning through Energy Minimization
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:5570-5582
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SE(3) Equivariant Graph Neural Networks with Complete Local Frames
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:5583-5608
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A Context-Integrated Transformer-Based Neural Network for Auction Design
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:5609-5626
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Augment with Care: Contrastive Learning for Combinatorial Problems
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:5627-5642
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Parametric Visual Program Induction with Function Modularization
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:5643-5658
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Bayesian Deep Embedding Topic Meta-Learner
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:5659-5670
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Deletion Robust Submodular Maximization over Matroids
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:5671-5693
From data to functa: Your data point is a function and you can treat it like one
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:5694-5725
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Efficient Low Rank Convex Bounds for Pairwise Discrete Graphical Models
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:5726-5741
Robust Counterfactual Explanations for Tree-Based Ensembles
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:5742-5756
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On the Difficulty of Defending Self-Supervised Learning against Model Extraction
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:5757-5776
LIMO: Latent Inceptionism for Targeted Molecule Generation
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:5777-5792
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Inductive Biases and Variable Creation in Self-Attention Mechanisms
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:5793-5831
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Provable Reinforcement Learning with a Short-Term Memory
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:5832-5850
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Sparsity in Partially Controllable Linear Systems
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:5851-5860
FedNew: A Communication-Efficient and Privacy-Preserving Newton-Type Method for Federated Learning
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:5861-5877
pathGCN: Learning General Graph Spatial Operators from Paths
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:5878-5891
Discrete Tree Flows via Tree-Structured Permutations
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:5892-5923
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For Learning in Symmetric Teams, Local Optima are Global Nash Equilibria
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:5924-5943
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Streaming Algorithm for Monotone k-Submodular Maximization with Cardinality Constraints
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:5944-5967
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Towards Scaling Difference Target Propagation by Learning Backprop Targets
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:5968-5987
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Understanding Dataset Difficulty with $\mathcal{V}$-Usable Information
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:5988-6008
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Head2Toe: Utilizing Intermediate Representations for Better Transfer Learning
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:6009-6033
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Variational Sparse Coding with Learned Thresholding
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:6034-6058
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Training Discrete Deep Generative Models via Gapped Straight-Through Estimator
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:6059-6073
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DRIBO: Robust Deep Reinforcement Learning via Multi-View Information Bottleneck
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:6074-6102
Generalized Data Distribution Iteration
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:6103-6184
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Variational Wasserstein gradient flow
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:6185-6215
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Data Determines Distributional Robustness in Contrastive Language Image Pre-training (CLIP)
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:6216-6234
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Bayesian Continuous-Time Tucker Decomposition
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:6235-6245
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Byzantine Machine Learning Made Easy By Resilient Averaging of Momentums
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:6246-6283
An Equivalence Between Data Poisoning and Byzantine Gradient Attacks
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:6284-6323
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Investigating Generalization by Controlling Normalized Margin
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:6324-6336
Kernelized Multiplicative Weights for 0/1-Polyhedral Games: Bridging the Gap Between Learning in Extensive-Form and Normal-Form Games
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:6337-6357
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Local Linear Convergence of Douglas-Rachford for Linear Programming: a Probabilistic Analysis
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:6358-6372
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Matching Structure for Dual Learning
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:6373-6391
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Cascaded Gaps: Towards Logarithmic Regret for Risk-Sensitive Reinforcement Learning
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:6392-6417
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Private frequency estimation via projective geometry
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:6418-6433
An Intriguing Property of Geophysics Inversion
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:6434-6446
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Principled Knowledge Extrapolation with GANs
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:6447-6464
A Resilient Distributed Boosting Algorithm
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:6465-6473
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Model-Value Inconsistency as a Signal for Epistemic Uncertainty
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:6474-6498
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Coordinated Double Machine Learning
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:6499-6513
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Conformal Prediction Sets with Limited False Positives
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:6514-6532
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Fast Population-Based Reinforcement Learning on a Single Machine
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:6533-6547
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Fast Relative Entropy Coding with A* coding
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:6548-6577
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Contrastive Mixture of Posteriors for Counterfactual Inference, Data Integration and Fairness
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:6578-6621
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Label Ranking through Nonparametric Regression
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:6622-6659
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A Neural Tangent Kernel Perspective of GANs
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:6660-6704
Extracting Latent State Representations with Linear Dynamics from Rich Observations
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:6705-6725
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SPDY: Accurate Pruning with Speedup Guarantees
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:6726-6743
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Revisiting the Effects of Stochasticity for Hamiltonian Samplers
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:6744-6778
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Bregman Neural Networks
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:6779-6792
(Non-)Convergence Results for Predictive Coding Networks
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:6793-6810
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Scaling Structured Inference with Randomization
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:6811-6828
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Greedy when Sure and Conservative when Uncertain about the Opponents
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:6829-6848
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DepthShrinker: A New Compression Paradigm Towards Boosting Real-Hardware Efficiency of Compact Neural Networks
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:6849-6862
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Revisiting Some Common Practices in Cooperative Multi-Agent Reinforcement Learning
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:6863-6877
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$p$-Laplacian Based Graph Neural Networks
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:6878-6917
Why Should I Trust You, Bellman? The Bellman Error is a Poor Replacement for Value Error
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:6918-6943
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Robin Hood and Matthew Effects: Differential Privacy Has Disparate Impact on Synthetic Data
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:6944-6959
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The Complexity of k-Means Clustering when Little is Known
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:6960-6987
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IDYNO: Learning Nonparametric DAGs from Interventional Dynamic Data
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:6988-7001
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Loss Function Learning for Domain Generalization by Implicit Gradient
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:7002-7016
On the Convergence of Local Stochastic Compositional Gradient Descent with Momentum
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:7017-7035
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Deep Reference Priors: What is the best way to pretrain a model?
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:7036-7051
On the Equivalence Between Temporal and Static Equivariant Graph Representations
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:7052-7076
Generalizing Gaussian Smoothing for Random Search
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:7077-7101
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Rethinking Image-Scaling Attacks: The Interplay Between Vulnerabilities in Machine Learning Systems
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:7102-7121
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Lazy Estimation of Variable Importance for Large Neural Networks
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:7122-7143
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Fast and Reliable Evaluation of Adversarial Robustness with Minimum-Margin Attack
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:7144-7163
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Value Function based Difference-of-Convex Algorithm for Bilevel Hyperparameter Selection Problems
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:7164-7182
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Learning to Incorporate Texture Saliency Adaptive Attention to Image Cartoonization
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:7183-7207
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Stochastic smoothing of the top-K calibrated hinge loss for deep imbalanced classification
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:7208-7222
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PAGE-PG: A Simple and Loopless Variance-Reduced Policy Gradient Method with Probabilistic Gradient Estimation
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:7223-7240
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The power of first-order smooth optimization for black-box non-smooth problems
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:7241-7265
A Functional Information Perspective on Model Interpretation
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:7266-7278
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UniRank: Unimodal Bandit Algorithms for Online Ranking
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:7279-7309
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Variational Inference with Locally Enhanced Bounds for Hierarchical Models
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:7310-7323
Inducing Causal Structure for Interpretable Neural Networks
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:7324-7338
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Achieving Minimax Rates in Pool-Based Batch Active Learning
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:7339-7367
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Near-Exact Recovery for Tomographic Inverse Problems via Deep Learning
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:7368-7381
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Online Learning for Min Sum Set Cover and Pandora’s Box
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:7382-7403
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Equivariance versus Augmentation for Spherical Images
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:7404-7421
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A Regret Minimization Approach to Multi-Agent Control
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:7422-7434
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Blocks Assemble! Learning to Assemble with Large-Scale Structured Reinforcement Learning
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:7435-7469
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Faster Privacy Accounting via Evolving Discretization
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:7470-7483
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Plug-In Inversion: Model-Agnostic Inversion for Vision with Data Augmentations
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:7484-7512
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Offline RL Policies Should Be Trained to be Adaptive
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:7513-7530
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Breaking the $\sqrtT$ Barrier: Instance-Independent Logarithmic Regret in Stochastic Contextual Linear Bandits
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:7531-7549
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SCHA-VAE: Hierarchical Context Aggregation for Few-Shot Generation
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:7550-7569
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A Joint Exponential Mechanism For Differentially Private Top-$k$
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:7570-7582
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Neuro-Symbolic Hierarchical Rule Induction
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:7583-7615
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It’s Raw! Audio Generation with State-Space Models
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:7616-7633
RankSim: Ranking Similarity Regularization for Deep Imbalanced Regression
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:7634-7649
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How to Fill the Optimum Set? Population Gradient Descent with Harmless Diversity
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:7650-7664
Partial Label Learning via Label Influence Function
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:7665-7678
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Secure Distributed Training at Scale
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:7679-7739
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Retrieval-Augmented Reinforcement Learning
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:7740-7765
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The State of Sparse Training in Deep Reinforcement Learning
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:7766-7792
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Causal Inference Through the Structural Causal Marginal Problem
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:7793-7824
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Mirror Learning: A Unifying Framework of Policy Optimisation
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:7825-7844
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Adapting k-means Algorithms for Outliers
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:7845-7886
Variational Mixtures of ODEs for Inferring Cellular Gene Expression Dynamics
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:7887-7901
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Learning Pseudometric-based Action Representations for Offline Reinforcement Learning
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:7902-7918
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NeuroFluid: Fluid Dynamics Grounding with Particle-Driven Neural Radiance Fields
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:7919-7929
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Fast-Rate PAC-Bayesian Generalization Bounds for Meta-Learning
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:7930-7948
Leveraging Approximate Symbolic Models for Reinforcement Learning via Skill Diversity
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:7949-7967
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Large-Scale Graph Neural Architecture Search
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:7968-7981
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Identifiability Conditions for Domain Adaptation
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:7982-7997
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A Parametric Class of Approximate Gradient Updates for Policy Optimization
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:7998-8015
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Provably Efficient Offline Reinforcement Learning for Partially Observable Markov Decision Processes
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:8016-8038
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No-Regret Learning in Partially-Informed Auctions
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:8039-8055
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Bounding Training Data Reconstruction in Private (Deep) Learning
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:8056-8071
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Adversarially trained neural representations are already as robust as biological neural representations
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:8072-8081
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Class-Imbalanced Semi-Supervised Learning with Adaptive Thresholding
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:8082-8094
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Deep Squared Euclidean Approximation to the Levenshtein Distance for DNA Storage
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:8095-8108
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Online Continual Learning through Mutual Information Maximization
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:8109-8126
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Fast Provably Robust Decision Trees and Boosting
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:8127-8144
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Understanding and Improving Knowledge Graph Embedding for Entity Alignment
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:8145-8156
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NISPA: Neuro-Inspired Stability-Plasticity Adaptation for Continual Learning in Sparse Networks
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:8157-8174
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Active Learning on a Budget: Opposite Strategies Suit High and Low Budgets
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:8175-8195
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You Only Cut Once: Boosting Data Augmentation with a Single Cut
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:8196-8212
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Scalable MCMC Sampling for Nonsymmetric Determinantal Point Processes
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:8213-8229
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G-Mixup: Graph Data Augmentation for Graph Classification
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:8230-8248
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Private Streaming SCO in $\ell_p$ geometry with Applications in High Dimensional Online Decision Making
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:8249-8279
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Off-Policy Reinforcement Learning with Delayed Rewards
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:8280-8303
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Adversarial Attacks on Gaussian Process Bandits
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:8304-8329
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Random Gegenbauer Features for Scalable Kernel Methods
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:8330-8358
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Stochastic Reweighted Gradient Descent
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:8359-8374
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Dual Perspective of Label-Specific Feature Learning for Multi-Label Classification
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:8375-8386
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Temporal Difference Learning for Model Predictive Control
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:8387-8406
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Bisimulation Makes Analogies in Goal-Conditioned Reinforcement Learning
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:8407-8426
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TURF: Two-Factor, Universal, Robust, Fast Distribution Learning Algorithm
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:8427-8445
Contextual Information-Directed Sampling
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:8446-8464
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GSmooth: Certified Robustness against Semantic Transformations via Generalized Randomized Smoothing
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:8465-8483
Implicit Regularization with Polynomial Growth in Deep Tensor Factorization
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:8484-8501
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Strategic Instrumental Variable Regression: Recovering Causal Relationships From Strategic Responses
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:8502-8522
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C*-algebra Net: A New Approach Generalizing Neural Network Parameters to C*-algebra
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:8523-8534
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General-purpose, long-context autoregressive modeling with Perceiver AR
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:8535-8558
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On Distribution Shift in Learning-based Bug Detectors
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:8559-8580
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GNNRank: Learning Global Rankings from Pairwise Comparisons via Directed Graph Neural Networks
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:8581-8612
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Exploring the Gap between Collapsed & Whitened Features in Self-Supervised Learning
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:8613-8634
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Sparse Double Descent: Where Network Pruning Aggravates Overfitting
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:8635-8659
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A Reduction from Linear Contextual Bandits Lower Bounds to Estimations Lower Bounds
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:8660-8677
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HyperPrompt: Prompt-based Task-Conditioning of Transformers
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:8678-8690
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Label-Descriptive Patterns and Their Application to Characterizing Classification Errors
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:8691-8707
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NOMU: Neural Optimization-based Model Uncertainty
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:8708-8758
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Scaling Out-of-Distribution Detection for Real-World Settings
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:8759-8773
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Generalization Bounds using Lower Tail Exponents in Stochastic Optimizers
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:8774-8795
Unsupervised Detection of Contextualized Embedding Bias with Application to Ideology
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:8796-8810
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Neural Laplace: Learning diverse classes of differential equations in the Laplace domain
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:8811-8832
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Deep Hierarchy in Bandits
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:8833-8851
DAdaQuant: Doubly-adaptive quantization for communication-efficient Federated Learning
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:8852-8866
Equivariant Diffusion for Molecule Generation in 3D
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:8867-8887
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Conditional GANs with Auxiliary Discriminative Classifier
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:8888-8902
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AdAUC: End-to-end Adversarial AUC Optimization Against Long-tail Problems
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:8903-8925
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Wide Bayesian neural networks have a simple weight posterior: theory and accelerated sampling
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:8926-8945
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Learning inverse folding from millions of predicted structures
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:8946-8970
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Nearly Minimax Optimal Reinforcement Learning with Linear Function Approximation
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:8971-9019
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Neuron Dependency Graphs: A Causal Abstraction of Neural Networks
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:9020-9040
Policy Diagnosis via Measuring Role Diversity in Cooperative Multi-agent RL
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:9041-9071
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On the Role of Discount Factor in Offline Reinforcement Learning
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:9072-9098
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Transformer Quality in Linear Time
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:9099-9117
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Language Models as Zero-Shot Planners: Extracting Actionable Knowledge for Embodied Agents
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:9118-9147
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Forward Operator Estimation in Generative Models with Kernel Transfer Operators
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:9148-9172
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Adaptive Best-of-Both-Worlds Algorithm for Heavy-Tailed Multi-Armed Bandits
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:9173-9200
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Frustratingly Easy Transferability Estimation
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:9201-9225
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Modality Competition: What Makes Joint Training of Multi-modal Network Fail in Deep Learning? (Provably)
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:9226-9259
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Action-Sufficient State Representation Learning for Control with Structural Constraints
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:9260-9279
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3DLinker: An E(3) Equivariant Variational Autoencoder for Molecular Linker Design
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:9280-9294
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SDQ: Stochastic Differentiable Quantization with Mixed Precision
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:9295-9309
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Tackling Data Heterogeneity: A New Unified Framework for Decentralized SGD with Sample-induced Topology
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:9310-9345
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Efficient Representation Learning via Adaptive Context Pooling
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:9346-9355
On the Learning of Non-Autoregressive Transformers
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:9356-9376
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Going Deeper into Permutation-Sensitive Graph Neural Networks
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:9377-9409
Directed Acyclic Transformer for Non-Autoregressive Machine Translation
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:9410-9428
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Unsupervised Ground Metric Learning Using Wasserstein Singular Vectors
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:9429-9443
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Robust Kernel Density Estimation with Median-of-Means principle
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:9444-9465
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A data-driven approach for learning to control computers
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:9466-9482
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Proximal Denoiser for Convergent Plug-and-Play Optimization with Nonconvex Regularization
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:9483-9505
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Inverse Contextual Bandits: Learning How Behavior Evolves over Time
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:9506-9524
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Datamodels: Understanding Predictions with Data and Data with Predictions
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:9525-9587
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Parsimonious Learning-Augmented Caching
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:9588-9601
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Bayesian Optimization for Distributionally Robust Chance-constrained Problem
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:9602-9621
LeNSE: Learning To Navigate Subgraph Embeddings for Large-Scale Combinatorial Optimisation
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:9622-9638
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The Dual Form of Neural Networks Revisited: Connecting Test Time Predictions to Training Patterns via Spotlights of Attention
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:9639-9659
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A Modern Self-Referential Weight Matrix That Learns to Modify Itself
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:9660-9677
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Revisiting Online Submodular Minimization: Gap-Dependent Regret Bounds, Best of Both Worlds and Adversarial Robustness
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:9678-9694
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Modeling Strong and Human-Like Gameplay with KL-Regularized Search
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:9695-9728
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A deep convolutional neural network that is invariant to time rescaling
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:9729-9738
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Input Dependent Sparse Gaussian Processes
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:9739-9759
Regret Minimization with Performative Feedback
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:9760-9785
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Biological Sequence Design with GFlowNets
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:9786-9801
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Combining Diverse Feature Priors
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:9802-9832
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Training Your Sparse Neural Network Better with Any Mask
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:9833-9844
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Sequential Covariate Shift Detection Using Classifier Two-Sample Tests
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:9845-9880
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Surrogate Likelihoods for Variational Annealed Importance Sampling
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:9881-9901
Planning with Diffusion for Flexible Behavior Synthesis
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:9902-9915
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HyperImpute: Generalized Iterative Imputation with Automatic Model Selection
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:9916-9937
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Mitigating Modality Collapse in Multimodal VAEs via Impartial Optimization
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:9938-9964
Towards understanding how momentum improves generalization in deep learning
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:9965-10040
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MASER: Multi-Agent Reinforcement Learning with Subgoals Generated from Experience Replay Buffer
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:10041-10052
An Exact Symbolic Reduction of Linear Smart Predict+Optimize to Mixed Integer Linear Programming
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:10053-10067
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Agnostic Learnability of Halfspaces via Logistic Loss
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:10068-10103
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Improving Policy Optimization with Generalist-Specialist Learning
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:10104-10119
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Translatotron 2: High-quality direct speech-to-speech translation with voice preservation
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:10120-10134
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Online Learning and Pricing with Reusable Resources: Linear Bandits with Sub-Exponential Rewards
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:10135-10160
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The Role of Deconfounding in Meta-learning
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:10161-10176
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Subspace Learning for Effective Meta-Learning
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:10177-10194
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Optimal Algorithms for Stochastic Multi-Level Compositional Optimization
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:10195-10216
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Antibody-Antigen Docking and Design via Hierarchical Structure Refinement
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:10217-10227
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Sharpened Quasi-Newton Methods: Faster Superlinear Rate and Larger Local Convergence Neighborhood
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:10228-10250
The Power of Exploiter: Provable Multi-Agent RL in Large State Spaces
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:10251-10279
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Domain Adaptation for Time Series Forecasting via Attention Sharing
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:10280-10297
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Accelerated Federated Learning with Decoupled Adaptive Optimization
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:10298-10322
Supervised Off-Policy Ranking
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:10323-10339
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Input-agnostic Certified Group Fairness via Gaussian Parameter Smoothing
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:10340-10361
Score-based Generative Modeling of Graphs via the System of Stochastic Differential Equations
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:10362-10383
Choosing Answers in Epsilon-Best-Answer Identification for Linear Bandits
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:10384-10430
Robust Fine-Tuning of Deep Neural Networks with Hessian-based Generalization Guarantees
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:10431-10461
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Robust alignment of cross-session recordings of neural population activity by behaviour via unsupervised domain adaptation
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:10462-10475
On Measuring Causal Contributions via do-interventions
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:10476-10501
Efficient Approximate Inference for Stationary Kernel on Frequency Domain
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:10502-10538
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Sketching Algorithms and Lower Bounds for Ridge Regression
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:10539-10556
Flashlight: Enabling Innovation in Tools for Machine Learning
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:10557-10574
Learning-based Optimisation of Particle Accelerators Under Partial Observability Without Real-World Training
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:10575-10585
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Stochastic Deep Networks with Linear Competing Units for Model-Agnostic Meta-Learning
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:10586-10597
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Doubly Robust Distributionally Robust Off-Policy Evaluation and Learning
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:10598-10632
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Improved Rates for Differentially Private Stochastic Convex Optimization with Heavy-Tailed Data
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:10633-10660
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Comprehensive Analysis of Negative Sampling in Knowledge Graph Representation Learning
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:10661-10675
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Matching Learned Causal Effects of Neural Networks with Domain Priors
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:10676-10696
Deduplicating Training Data Mitigates Privacy Risks in Language Models
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:10697-10707
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Lyapunov Density Models: Constraining Distribution Shift in Learning-Based Control
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:10708-10733
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Forget-free Continual Learning with Winning Subnetworks
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:10734-10750
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Differentially Private Approximate Quantiles
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:10751-10761
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Simultaneous Graph Signal Clustering and Graph Learning
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:10762-10772
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Composing Partial Differential Equations with Physics-Aware Neural Networks
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:10773-10801
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Meta-Learning Hypothesis Spaces for Sequential Decision-making
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:10802-10824
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FOCUS: Familiar Objects in Common and Uncommon Settings
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:10825-10847
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Training OOD Detectors in their Natural Habitats
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:10848-10865
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Robustness Implies Generalization via Data-Dependent Generalization Bounds
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:10866-10894
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Generating Distributional Adversarial Examples to Evade Statistical Detectors
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:10895-10911
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Secure Quantized Training for Deep Learning
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:10912-10938
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A Convergent and Dimension-Independent Min-Max Optimization Algorithm
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:10939-10973
Neural Network Poisson Models for Behavioural and Neural Spike Train Data
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:10974-10996
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Federated Reinforcement Learning: Linear Speedup Under Markovian Sampling
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:10997-11057
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Multi-Level Branched Regularization for Federated Learning
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:11058-11073
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Learning fair representation with a parametric integral probability metric
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:11074-11101
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Dataset Condensation via Efficient Synthetic-Data Parameterization
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:11102-11118
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Guided-TTS: A Diffusion Model for Text-to-Speech via Classifier Guidance
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:11119-11133
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Variational On-the-Fly Personalization
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:11134-11147
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Fisher SAM: Information Geometry and Sharpness Aware Minimisation
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:11148-11161
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ViT-NeT: Interpretable Vision Transformers with Neural Tree Decoder
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:11162-11172
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Sanity Simulations for Saliency Methods
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:11173-11200
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Soft Truncation: A Universal Training Technique of Score-based Diffusion Model for High Precision Score Estimation
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:11201-11228
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Rotting Infinitely Many-Armed Bandits
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:11229-11254
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Accelerated Gradient Methods for Geodesically Convex Optimization: Tractable Algorithms and Convergence Analysis
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:11255-11282
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Generalizing to New Physical Systems via Context-Informed Dynamics Model
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:11283-11301
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SoQal: Selective Oracle Questioning for Consistency Based Active Learning of Cardiac Signals
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:11302-11340
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Curriculum Reinforcement Learning via Constrained Optimal Transport
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:11341-11358
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Exploiting Redundancy: Separable Group Convolutional Networks on Lie Groups
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:11359-11386
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Revisiting Contrastive Learning through the Lens of Neighborhood Component Analysis: an Integrated Framework
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:11387-11412
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Transfer Learning In Differential Privacy’s Hybrid-Model
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:11413-11429
Markov Chain Monte Carlo for Continuous-Time Switching Dynamical Systems
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:11430-11454
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Partial disentanglement for domain adaptation
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:11455-11472
Simultaneously Learning Stochastic and Adversarial Bandits with General Graph Feedback
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:11473-11482
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Adaptive Data Analysis with Correlated Observations
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:11483-11498
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Controlling Conditional Language Models without Catastrophic Forgetting
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:11499-11528
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Batch Greenkhorn Algorithm for Entropic-Regularized Multimarginal Optimal Transport: Linear Rate of Convergence and Iteration Complexity
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:11529-11558
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Certified Adversarial Robustness Under the Bounded Support Set
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:11559-11597
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Exact Learning of Preference Structure: Single-peaked Preferences and Beyond
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:11598-11612
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Reconstructing Nonlinear Dynamical Systems from Multi-Modal Time Series
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:11613-11633
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Probabilistic ODE Solutions in Millions of Dimensions
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:11634-11649
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Active Nearest Neighbor Regression Through Delaunay Refinement
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:11650-11664
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Functional Generalized Empirical Likelihood Estimation for Conditional Moment Restrictions
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:11665-11682
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Calibrated and Sharp Uncertainties in Deep Learning via Density Estimation
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:11683-11693
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ActiveHedge: Hedge meets Active Learning
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:11694-11709
Balancing Discriminability and Transferability for Source-Free Domain Adaptation
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:11710-11728
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Showing Your Offline Reinforcement Learning Work: Online Evaluation Budget Matters
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:11729-11752
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Equivariant Priors for compressed sensing with unknown orientation
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:11753-11771
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Coordinated Attacks against Contextual Bandits: Fundamental Limits and Defense Mechanisms
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:11772-11789
Large Batch Experience Replay
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:11790-11813
FedScale: Benchmarking Model and System Performance of Federated Learning at Scale
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:11814-11827
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Smoothed Adaptive Weighting for Imbalanced Semi-Supervised Learning: Improve Reliability Against Unknown Distribution Data
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:11828-11843
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Functional Output Regression with Infimal Convolution: Exploring the Huber and $ε$-insensitive Losses
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:11844-11867
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Tell me why! Explanations support learning relational and causal structure
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:11868-11890
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Generative Cooperative Networks for Natural Language Generation
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:11891-11905
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DSTAGNN: Dynamic Spatial-Temporal Aware Graph Neural Network for Traffic Flow Forecasting
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:11906-11917
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Cooperative Online Learning in Stochastic and Adversarial MDPs
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:11918-11968
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PINs: Progressive Implicit Networks for Multi-Scale Neural Representations
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:11969-11984
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Co-training Improves Prompt-based Learning for Large Language Models
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:11985-12003
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Goal Misgeneralization in Deep Reinforcement Learning
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:12004-12019
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Marginal Tail-Adaptive Normalizing Flows
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:12020-12048
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Bregman Proximal Langevin Monte Carlo via Bregman-Moreau Envelopes
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:12049-12077
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Scalable Deep Reinforcement Learning Algorithms for Mean Field Games
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:12078-12095
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Implicit Bias of Linear Equivariant Networks
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:12096-12125
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Differentially Private Maximal Information Coefficients
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:12126-12163
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Entropic Gromov-Wasserstein between Gaussian Distributions
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:12164-12203
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Neurocoder: General-Purpose Computation Using Stored Neural Programs
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:12204-12221
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Convergence of Policy Gradient for Entropy Regularized MDPs with Neural Network Approximation in the Mean-Field Regime
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:12222-12252
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A Random Matrix Analysis of Data Stream Clustering: Coping With Limited Memory Resources
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:12253-12281
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Neural Tangent Kernel Analysis of Deep Narrow Neural Networks
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:12282-12351
Dataset Condensation with Contrastive Signals
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:12352-12364
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Confidence Score for Source-Free Unsupervised Domain Adaptation
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:12365-12377
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A Statistical Manifold Framework for Point Cloud Data
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:12378-12402
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Low-Complexity Deep Convolutional Neural Networks on Fully Homomorphic Encryption Using Multiplexed Parallel Convolutions
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:12403-12422
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Statistical inference with implicit SGD: proximal Robbins-Monro vs. Polyak-Ruppert
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:12423-12454
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Maslow’s Hammer in Catastrophic Forgetting: Node Re-Use vs. Node Activation
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:12455-12477
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Query-Efficient and Scalable Black-Box Adversarial Attacks on Discrete Sequential Data via Bayesian Optimization
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:12478-12497
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Least Squares Estimation using Sketched Data with Heteroskedastic Errors
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:12498-12520
Why the Rich Get Richer? On the Balancedness of Random Partition Models
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:12521-12541
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Model Selection in Batch Policy Optimization
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:12542-12569
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Supervised Learning with General Risk Functionals
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:12570-12592
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Generalized Strategic Classification and the Case of Aligned Incentives
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:12593-12618
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A Simple Unified Framework for High Dimensional Bandit Problems
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:12619-12655
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Robust Training of Neural Networks Using Scale Invariant Architectures
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:12656-12684
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Spatial-Channel Token Distillation for Vision MLPs
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:12685-12695
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An Analytical Update Rule for General Policy Optimization
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:12696-12716
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On Convergence of Gradient Descent Ascent: A Tight Local Analysis
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:12717-12740
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On the Finite-Time Performance of the Knowledge Gradient Algorithm
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:12741-12764
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Phasic Self-Imitative Reduction for Sparse-Reward Goal-Conditioned Reinforcement Learning
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:12765-12781
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G$^2$CN: Graph Gaussian Convolution Networks with Concentrated Graph Filters
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:12782-12796
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Decomposing Temporal High-Order Interactions via Latent ODEs
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:12797-12812
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Neural Inverse Transform Sampler
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:12813-12825
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PLATINUM: Semi-Supervised Model Agnostic Meta-Learning using Submodular Mutual Information
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:12826-12842
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Deconfounded Value Decomposition for Multi-Agent Reinforcement Learning
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:12843-12856
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C-MinHash: Improving Minwise Hashing with Circulant Permutation
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:12857-12887
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BLIP: Bootstrapping Language-Image Pre-training for Unified Vision-Language Understanding and Generation
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:12888-12900
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Restarted Nonconvex Accelerated Gradient Descent: No More Polylogarithmic Factor in the $O(ε^-7/4)$ Complexity
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:12901-12916
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Achieving Fairness at No Utility Cost via Data Reweighing with Influence
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:12917-12930
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High Probability Guarantees for Nonconvex Stochastic Gradient Descent with Heavy Tails
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:12931-12963
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MetAug: Contrastive Learning via Meta Feature Augmentation
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:12964-12978
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PMIC: Improving Multi-Agent Reinforcement Learning with Progressive Mutual Information Collaboration
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:12979-12997
CerDEQ: Certifiable Deep Equilibrium Model
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:12998-13013
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Generalization Guarantee of Training Graph Convolutional Networks with Graph Topology Sampling
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:13014-13051
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Let Invariant Rationale Discovery Inspire Graph Contrastive Learning
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:13052-13065
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Difference Advantage Estimation for Multi-Agent Policy Gradients
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:13066-13085
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Private Adaptive Optimization with Side information
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:13086-13105
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Permutation Search of Tensor Network Structures via Local Sampling
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:13106-13124
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Hessian-Free High-Resolution Nesterov Acceleration For Sampling
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:13125-13162
Double Sampling Randomized Smoothing
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:13163-13208
HousE: Knowledge Graph Embedding with Householder Parameterization
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:13209-13224
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Learning Multiscale Transformer Models for Sequence Generation
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:13225-13241
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Finding Global Homophily in Graph Neural Networks When Meeting Heterophily
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:13242-13256
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Fat–Tailed Variational Inference with Anisotropic Tail Adaptive Flows
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:13257-13270
Exploring and Exploiting Hubness Priors for High-Quality GAN Latent Sampling
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:13271-13284
Reducing Variance in Temporal-Difference Value Estimation via Ensemble of Deep Networks
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:13285-13301
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TSPipe: Learn from Teacher Faster with Pipelines
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:13302-13312
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Order Constraints in Optimal Transport
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:13313-13333
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Flow-Guided Sparse Transformer for Video Deblurring
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:13334-13343
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Federated Learning with Positive and Unlabeled Data
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:13344-13355
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Decentralized Online Convex Optimization in Networked Systems
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:13356-13393
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Unsupervised Flow-Aligned Sequence-to-Sequence Learning for Video Restoration
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:13394-13404
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Constrained Gradient Descent: A Powerful and Principled Evasion Attack Against Neural Networks
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:13405-13430
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Learning Augmented Binary Search Trees
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:13431-13440
Online Nonsubmodular Minimization with Delayed Costs: From Full Information to Bandit Feedback
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:13441-13467
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Measuring the Effect of Training Data on Deep Learning Predictions via Randomized Experiments
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:13468-13504
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Interactively Learning Preference Constraints in Linear Bandits
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:13505-13527
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Delayed Reinforcement Learning by Imitation
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:13528-13556
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CITRIS: Causal Identifiability from Temporal Intervened Sequences
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:13557-13603
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StreamingQA: A Benchmark for Adaptation to New Knowledge over Time in Question Answering Models
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:13604-13622
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Distributionally Robust $Q$-Learning
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:13623-13643
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Constrained Variational Policy Optimization for Safe Reinforcement Learning
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:13644-13668
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Benefits of Overparameterized Convolutional Residual Networks: Function Approximation under Smoothness Constraint
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:13669-13703
Boosting Graph Structure Learning with Dummy Nodes
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:13704-13716
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Equivalence Analysis between Counterfactual Regret Minimization and Online Mirror Descent
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:13717-13745
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Deep Probability Estimation
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:13746-13781
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Gating Dropout: Communication-efficient Regularization for Sparsely Activated Transformers
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:13782-13792
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Simplex Neural Population Learning: Any-Mixture Bayes-Optimality in Symmetric Zero-sum Games
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:13793-13806
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Rethinking Attention-Model Explainability through Faithfulness Violation Test
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:13807-13824
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Optimization-Derived Learning with Essential Convergence Analysis of Training and Hyper-training
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:13825-13856
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Deep Neural Network Fusion via Graph Matching with Applications to Model Ensemble and Federated Learning
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:13857-13869
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Welfare Maximization in Competitive Equilibrium: Reinforcement Learning for Markov Exchange Economy
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:13870-13911
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Generating 3D Molecules for Target Protein Binding
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:13912-13924
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Communication-efficient Distributed Learning for Large Batch Optimization
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:13925-13946
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Adaptive Accelerated (Extra-)Gradient Methods with Variance Reduction
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:13947-13994
REvolveR: Continuous Evolutionary Models for Robot-to-robot Policy Transfer
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:13995-14007
Kill a Bird with Two Stones: Closing the Convergence Gaps in Non-Strongly Convex Optimization by Directly Accelerated SVRG with Double Compensation and Snapshots
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:14008-14035
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Learning Markov Games with Adversarial Opponents: Efficient Algorithms and Fundamental Limits
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:14036-14053
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Local Augmentation for Graph Neural Networks
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:14054-14072
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Asking for Knowledge (AFK): Training RL Agents to Query External Knowledge Using Language
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:14073-14093
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Learning from Demonstration: Provably Efficient Adversarial Policy Imitation with Linear Function Approximation
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:14094-14138
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GACT: Activation Compressed Training for Generic Network Architectures
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:14139-14152
Robust Training under Label Noise by Over-parameterization
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:14153-14172
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Plan Your Target and Learn Your Skills: Transferable State-Only Imitation Learning via Decoupled Policy Optimization
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:14173-14196
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On the Impossibility of Learning to Cooperate with Adaptive Partner Strategies in Repeated Games
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:14197-14209
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AutoIP: A United Framework to Integrate Physics into Gaussian Processes
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:14210-14222
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Bayesian Model Selection, the Marginal Likelihood, and Generalization
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:14223-14247
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Feature Learning and Signal Propagation in Deep Neural Networks
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:14248-14282
Fluctuations, Bias, Variance & Ensemble of Learners: Exact Asymptotics for Convex Losses in High-Dimension
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:14283-14314
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A Single-Loop Gradient Descent and Perturbed Ascent Algorithm for Nonconvex Functional Constrained Optimization
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:14315-14357
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Additive Gaussian Processes Revisited
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:14358-14383
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ModLaNets: Learning Generalisable Dynamics via Modularity and Physical Inductive Bias
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:14384-14397
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Model-Free Opponent Shaping
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:14398-14411
Multi-slots Online Matching with High Entropy
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:14412-14428
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Maximum Likelihood Training for Score-based Diffusion ODEs by High Order Denoising Score Matching
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:14429-14460
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Orchestra: Unsupervised Federated Learning via Globally Consistent Clustering
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:14461-14484
A Rigorous Study of Integrated Gradients Method and Extensions to Internal Neuron Attributions
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:14485-14508
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BAMDT: Bayesian Additive Semi-Multivariate Decision Trees for Nonparametric Regression
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:14509-14526
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Disentangled Federated Learning for Tackling Attributes Skew via Invariant Aggregation and Diversity Transferring
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:14527-14541
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Channel Importance Matters in Few-Shot Image Classification
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:14542-14559
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Learning Dynamics and Generalization in Deep Reinforcement Learning
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:14560-14581
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On Finite-Sample Identifiability of Contrastive Learning-Based Nonlinear Independent Component Analysis
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:14582-14600
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Pessimism meets VCG: Learning Dynamic Mechanism Design via Offline Reinforcement Learning
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:14601-14638
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Versatile Offline Imitation from Observations and Examples via Regularized State-Occupancy Matching
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:14639-14663
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Quantification and Analysis of Layer-wise and Pixel-wise Information Discarding
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:14664-14698
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Interpretable Neural Networks with Frank-Wolfe: Sparse Relevance Maps and Relevance Orderings
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:14699-14716
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A Tighter Analysis of Spectral Clustering, and Beyond
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:14717-14742
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Zero-Shot Reward Specification via Grounded Natural Language
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:14743-14752
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Feature selection using e-values
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:14753-14773
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Knowledge-Grounded Self-Rationalization via Extractive and Natural Language Explanations
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:14786-14801
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Nonparametric Involutive Markov Chain Monte Carlo
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:14802-14859
Architecture Agnostic Federated Learning for Neural Networks
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:14860-14870
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Robustness in Multi-Objective Submodular Optimization: a Quantile Approach
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:14871-14886
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More Efficient Sampling for Tensor Decomposition With Worst-Case Guarantees
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:14887-14917
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Unaligned Supervision for Automatic Music Transcription in The Wild
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:14918-14934
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Decision-Focused Learning: Through the Lens of Learning to Rank
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:14935-14947
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Differentially Private Coordinate Descent for Composite Empirical Risk Minimization
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:14948-14978
Refined Convergence Rates for Maximum Likelihood Estimation under Finite Mixture Models
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:14979-15006
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On Improving Model-Free Algorithms for Decentralized Multi-Agent Reinforcement Learning
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:15007-15049
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On the Effects of Artificial Data Modification
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:15050-15069
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Personalized Federated Learning through Local Memorization
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:15070-15092
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Nested Bandits
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:15093-15121
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Closed-Form Diffeomorphic Transformations for Time Series Alignment
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:15122-15158
SPECTRE: Spectral Conditioning Helps to Overcome the Expressivity Limits of One-shot Graph Generators
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:15159-15179
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Modular Conformal Calibration
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:15180-15195
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Continual Repeated Annealed Flow Transport Monte Carlo
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:15196-15219
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How to Stay Curious while avoiding Noisy TVs using Aleatoric Uncertainty Estimation
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:15220-15240
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How to Steer Your Adversary: Targeted and Efficient Model Stealing Defenses with Gradient Redirection
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:15241-15254
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Quant-BnB: A Scalable Branch-and-Bound Method for Optimal Decision Trees with Continuous Features
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:15255-15277
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Optimizing Tensor Network Contraction Using Reinforcement Learning
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:15278-15292
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Causal Transformer for Estimating Counterfactual Outcomes
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:15293-15329
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Steerable 3D Spherical Neurons
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:15330-15339
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Transformers are Meta-Reinforcement Learners
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:15340-15359
ButterflyFlow: Building Invertible Layers with Butterfly Matrices
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:15360-15375
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In defense of dual-encoders for neural ranking
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:15376-15400
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Equivariant Quantum Graph Circuits
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:15401-15420
Stochastic Rising Bandits
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:15421-15457
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Minimizing Control for Credit Assignment with Strong Feedback
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:15458-15483
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A Dynamical System Perspective for Lipschitz Neural Networks
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:15484-15500
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Distribution Regression with Sliced Wasserstein Kernels
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:15501-15523
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Interpretable and Generalizable Graph Learning via Stochastic Attention Mechanism
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:15524-15543
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Modeling Structure with Undirected Neural Networks
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:15544-15560
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Universal Hopfield Networks: A General Framework for Single-Shot Associative Memory Models
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:15561-15583
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Learning Stochastic Shortest Path with Linear Function Approximation
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:15584-15629
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Prioritized Training on Points that are Learnable, Worth Learning, and not yet Learnt
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:15630-15649
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POEM: Out-of-Distribution Detection with Posterior Sampling
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:15650-15665
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A Simple Reward-free Approach to Constrained Reinforcement Learning
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:15666-15698
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Wide Neural Networks Forget Less Catastrophically
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:15699-15717
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Proximal and Federated Random Reshuffling
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:15718-15749
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ProxSkip: Yes! Local Gradient Steps Provably Lead to Communication Acceleration! Finally!
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:15750-15769
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Fast Convex Optimization for Two-Layer ReLU Networks: Equivalent Model Classes and Cone Decompositions
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:15770-15816
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Memory-Based Model Editing at Scale
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:15817-15831
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Invariant Ancestry Search
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:15832-15857
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Differentially Private Community Detection for Stochastic Block Models
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:15858-15894
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A Multi-objective / Multi-task Learning Framework Induced by Pareto Stationarity
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:15895-15907
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EqR: Equivariant Representations for Data-Efficient Reinforcement Learning
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:15908-15926
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Feature and Parameter Selection in Stochastic Linear Bandits
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:15927-15958
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Power-Law Escape Rate of SGD
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:15959-15975
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Rethinking Fano’s Inequality in Ensemble Learning
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:15976-16016
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SpeqNets: Sparsity-aware permutation-equivariant graph networks
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:16017-16042
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CtrlFormer: Learning Transferable State Representation for Visual Control via Transformer
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:16043-16061
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Generalized Beliefs for Cooperative AI
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:16062-16082
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Bounding the Width of Neural Networks via Coupled Initialization A Worst Case Analysis
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:16083-16122
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Constants Matter: The Performance Gains of Active Learning
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:16123-16173
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On the Generalization Analysis of Adversarial Learning
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:16174-16196
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Universal and data-adaptive algorithms for model selection in linear contextual bandits
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:16197-16222
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The Importance of Non-Markovianity in Maximum State Entropy Exploration
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:16223-16239
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PAC-Net: A Model Pruning Approach to Inductive Transfer Learning
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:16240-16252
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AutoSNN: Towards Energy-Efficient Spiking Neural Networks
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:16253-16269
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Implicit Bias of the Step Size in Linear Diagonal Neural Networks
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:16270-16295
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DNNR: Differential Nearest Neighbors Regression
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:16296-16317
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Overcoming Oscillations in Quantization-Aware Training
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:16318-16330
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Strategic Representation
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:16331-16352
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Improving Ensemble Distillation With Weight Averaging and Diversifying Perturbation
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:16353-16367
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Measuring Representational Robustness of Neural Networks Through Shared Invariances
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:16368-16382
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Tight and Robust Private Mean Estimation with Few Users
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:16383-16412
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Fast Aquatic Swimmer Optimization with Differentiable Projective Dynamics and Neural Network Hydrodynamic Models
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:16413-16427
Multi-Task Learning as a Bargaining Game
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:16428-16446
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Variational Inference for Infinitely Deep Neural Networks
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:16447-16461
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Stable Conformal Prediction Sets
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:16462-16479
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Discovering Generalizable Spatial Goal Representations via Graph-based Active Reward Learning
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:16480-16495
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Sublinear-Time Clustering Oracle for Signed Graphs
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:16496-16528
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Improved Regret for Differentially Private Exploration in Linear MDP
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:16529-16552
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A Framework for Learning to Request Rich and Contextually Useful Information from Humans
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:16553-16568
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Transformer Neural Processes: Uncertainty-Aware Meta Learning Via Sequence Modeling
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:16569-16594
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Improving Transformers with Probabilistic Attention Keys
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:16595-16621
On Transportation of Mini-batches: A Hierarchical Approach
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:16622-16655
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Improving Mini-batch Optimal Transport via Partial Transportation
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:16656-16690
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Recurrent Model-Free RL Can Be a Strong Baseline for Many POMDPs
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:16691-16723
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Optimal Estimation of Policy Gradient via Double Fitted Iteration
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:16724-16783
GLIDE: Towards Photorealistic Image Generation and Editing with Text-Guided Diffusion Models
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:16784-16804
Diffusion Models for Adversarial Purification
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:16805-16827
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The Primacy Bias in Deep Reinforcement Learning
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:16828-16847
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Causal Conceptions of Fairness and their Consequences
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:16848-16887
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Efficient Test-Time Model Adaptation without Forgetting
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:16888-16905
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Generative Trees: Adversarial and Copycat
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:16906-16951
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Path-Aware and Structure-Preserving Generation of Synthetically Accessible Molecules
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:16952-16968
Utilizing Expert Features for Contrastive Learning of Time-Series Representations
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:16969-16989
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Tranception: Protein Fitness Prediction with Autoregressive Transformers and Inference-time Retrieval
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:16990-17017
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Fast Finite Width Neural Tangent Kernel
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:17018-17044
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Multicoated Supermasks Enhance Hidden Networks
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:17045-17055
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Generalized Leverage Scores: Geometric Interpretation and Applications
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:17056-17070
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Practical Almost-Linear-Time Approximation Algorithms for Hybrid and Overlapping Graph Clustering
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:17071-17093
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Anticorrelated Noise Injection for Improved Generalization
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:17094-17116
Scalable Deep Gaussian Markov Random Fields for General Graphs
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:17117-17137
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Zero-shot AutoML with Pretrained Models
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:17138-17155
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History Compression via Language Models in Reinforcement Learning
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:17156-17185
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A Study on the Ramanujan Graph Property of Winning Lottery Tickets
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:17186-17201
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On Learning Mixture of Linear Regressions in the Non-Realizable Setting
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:17202-17220
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Plan Better Amid Conservatism: Offline Multi-Agent Reinforcement Learning with Actor Rectification
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:17221-17237
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A Unified Weight Initialization Paradigm for Tensorial Convolutional Neural Networks
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:17238-17257
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Robustness and Accuracy Could Be Reconcilable by (Proper) Definition
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:17258-17277
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Towards Coherent and Consistent Use of Entities in Narrative Generation
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:17278-17294
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Constrained Discrete Black-Box Optimization using Mixed-Integer Programming
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:17295-17322
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A Theoretical Comparison of Graph Neural Network Extensions
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:17323-17345
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Validating Causal Inference Methods
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:17346-17358
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The Unsurprising Effectiveness of Pre-Trained Vision Models for Control
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:17359-17371
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Learning Symmetric Embeddings for Equivariant World Models
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:17372-17389
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Blurs Behave Like Ensembles: Spatial Smoothings to Improve Accuracy, Uncertainty, and Robustness
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:17390-17419
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Exact Optimal Accelerated Complexity for Fixed-Point Iterations
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:17420-17457
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Kernel Methods for Radial Transformed Compositional Data with Many Zeros
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:17458-17472
Evolving Curricula with Regret-Based Environment Design
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:17473-17498
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Neural Language Models are not Born Equal to Fit Brain Data, but Training Helps
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:17499-17516
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A new similarity measure for covariate shift with applications to nonparametric regression
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:17517-17530
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Align-RUDDER: Learning From Few Demonstrations by Reward Redistribution
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:17531-17572
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POET: Training Neural Networks on Tiny Devices with Integrated Rematerialization and Paging
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:17573-17583
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Learning to Cut by Looking Ahead: Cutting Plane Selection via Imitation Learning
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:17584-17600
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Neural Network Pruning Denoises the Features and Makes Local Connectivity Emerge in Visual Tasks
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:17601-17626
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Branchformer: Parallel MLP-Attention Architectures to Capture Local and Global Context for Speech Recognition and Understanding
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:17627-17643
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Pocket2Mol: Efficient Molecular Sampling Based on 3D Protein Pockets
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:17644-17655
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Differentiable Top-k Classification Learning
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:17656-17668
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Multi-scale Feature Learning Dynamics: Insights for Double Descent
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:17669-17690
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A Differential Entropy Estimator for Training Neural Networks
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:17691-17715
Federated Learning with Partial Model Personalization
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:17716-17758
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Deep Networks on Toroids: Removing Symmetries Reveals the Structure of Flat Regions in the Landscape Geometry
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:17759-17781
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Geometric Multimodal Contrastive Representation Learning
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:17782-17800
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Constrained Offline Policy Optimization
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:17801-17810
Offline Meta-Reinforcement Learning with Online Self-Supervision
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:17811-17829
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Debiaser Beware: Pitfalls of Centering Regularized Transport Maps
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:17830-17847
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Adaptive Second Order Coresets for Data-efficient Machine Learning
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:17848-17869
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On the Practicality of Deterministic Epistemic Uncertainty
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:17870-17909
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A Simple Guard for Learned Optimizers
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:17910-17925
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Hardness and Algorithms for Robust and Sparse Optimization
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:17926-17944
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Nonlinear Feature Diffusion on Hypergraphs
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:17945-17958
Universal Joint Approximation of Manifolds and Densities by Simple Injective Flows
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:17959-17983
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The Teaching Dimension of Regularized Kernel Learners
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:17984-18002
ContentVec: An Improved Self-Supervised Speech Representation by Disentangling Speakers
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:18003-18017
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Interventional Contrastive Learning with Meta Semantic Regularizer
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:18018-18030
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Sample-Efficient Reinforcement Learning with loglog(T) Switching Cost
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:18031-18061
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Generalizing to Evolving Domains with Latent Structure-Aware Sequential Autoencoder
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:18062-18082
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Graph Neural Architecture Search Under Distribution Shifts
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:18083-18095
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Spectral Representation of Robustness Measures for Optimization Under Input Uncertainty
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:18096-18121
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Large-scale Stochastic Optimization of NDCG Surrogates for Deep Learning with Provable Convergence
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:18122-18152
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Latent Outlier Exposure for Anomaly Detection with Contaminated Data
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:18153-18167
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Contrastive UCB: Provably Efficient Contrastive Self-Supervised Learning in Online Reinforcement Learning
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:18168-18210
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Fast and Provable Nonconvex Tensor RPCA
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:18211-18249
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Generalized Federated Learning via Sharpness Aware Minimization
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:18250-18280
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Particle Transformer for Jet Tagging
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:18281-18292
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Winning the Lottery Ahead of Time: Efficient Early Network Pruning
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:18293-18309
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Convergence of Uncertainty Sampling for Active Learning
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:18310-18331
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DeepSpeed-MoE: Advancing Mixture-of-Experts Inference and Training to Power Next-Generation AI Scale
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:18332-18346
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Fishr: Invariant Gradient Variances for Out-of-Distribution Generalization
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:18347-18377
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A Closer Look at Smoothness in Domain Adversarial Training
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:18378-18399
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Linear Adversarial Concept Erasure
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:18400-18421
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Implicit Regularization in Hierarchical Tensor Factorization and Deep Convolutional Neural Networks
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:18422-18462
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One-Pass Algorithms for MAP Inference of Nonsymmetric Determinantal Point Processes
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:18463-18482
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Universality of Winning Tickets: A Renormalization Group Perspective
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:18483-18498
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The dynamics of representation learning in shallow, non-linear autoencoders
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:18499-18519
Proximal Exploration for Model-guided Protein Sequence Design
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:18520-18536
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Towards Theoretical Analysis of Transformation Complexity of ReLU DNNs
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:18537-18558
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Benchmarking and Analyzing Point Cloud Classification under Corruptions
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:18559-18575
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A Unified View on PAC-Bayes Bounds for Meta-Learning
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:18576-18595
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3PC: Three Point Compressors for Communication-Efficient Distributed Training and a Better Theory for Lazy Aggregation
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:18596-18648
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Robust SDE-Based Variational Formulations for Solving Linear PDEs via Deep Learning
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:18649-18666
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Probabilistically Robust Learning: Balancing Average and Worst-case Performance
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:18667-18686
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LyaNet: A Lyapunov Framework for Training Neural ODEs
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:18687-18703
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Short-Term Plasticity Neurons Learning to Learn and Forget
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:18704-18722
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Function-space Inference with Sparse Implicit Processes
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:18723-18740
Score Matching Enables Causal Discovery of Nonlinear Additive Noise Models
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:18741-18753
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Dual Decomposition of Convex Optimization Layers for Consistent Attention in Medical Images
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:18754-18769
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A Consistent and Efficient Evaluation Strategy for Attribution Methods
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:18770-18795
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Efficiently Learning the Topology and Behavior of a Networked Dynamical System Via Active Queries
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:18796-18808
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Learning to Infer Structures of Network Games
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:18809-18827
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Direct Behavior Specification via Constrained Reinforcement Learning
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:18828-18843
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Constraint-based graph network simulator
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:18844-18870
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Continual Learning via Sequential Function-Space Variational Inference
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:18871-18887
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Graph-Coupled Oscillator Networks
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:18888-18909
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Hindering Adversarial Attacks with Implicit Neural Representations
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:18910-18934
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Exploiting Independent Instruments: Identification and Distribution Generalization
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:18935-18958
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FedNL: Making Newton-Type Methods Applicable to Federated Learning
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:18959-19010
Versatile Dueling Bandits: Best-of-both World Analyses for Learning from Relative Preferences
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:19011-19026
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Optimal and Efficient Dynamic Regret Algorithms for Non-Stationary Dueling Bandits
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:19027-19049
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Unraveling Attention via Convex Duality: Analysis and Interpretations of Vision Transformers
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:19050-19088
Off-Policy Evaluation for Large Action Spaces via Embeddings
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:19089-19122
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Optimal Clipping and Magnitude-aware Differentiation for Improved Quantization-aware Training
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:19123-19138
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A Convergence Theory for SVGD in the Population Limit under Talagrand’s Inequality T1
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:19139-19152
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FITNESS: (Fine Tune on New and Similar Samples) to detect anomalies in streams with drift and outliers
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:19153-19177
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The Algebraic Path Problem for Graph Metrics
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:19178-19204
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LSB: Local Self-Balancing MCMC in Discrete Spaces
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:19205-19220
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PoF: Post-Training of Feature Extractor for Improving Generalization
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:19221-19230
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Re-evaluating Word Mover’s Distance
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:19231-19249
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Understanding Contrastive Learning Requires Incorporating Inductive Biases
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:19250-19286
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The Neural Race Reduction: Dynamics of Abstraction in Gated Networks
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:19287-19309
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Convergence Rates of Non-Convex Stochastic Gradient Descent Under a Generic Lojasiewicz Condition and Local Smoothness
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:19310-19327
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An Asymptotic Test for Conditional Independence using Analytic Kernel Embeddings
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:19328-19346
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Linear-Time Gromov Wasserstein Distances using Low Rank Couplings and Costs
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:19347-19365
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Streaming Inference for Infinite Feature Models
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:19366-19387
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Modeling Irregular Time Series with Continuous Recurrent Units
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:19388-19405
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Structure Preserving Neural Networks: A Case Study in the Entropy Closure of the Boltzmann Equation
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:19406-19433
Improving Robustness against Real-World and Worst-Case Distribution Shifts through Decision Region Quantification
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:19434-19449
Symmetric Machine Theory of Mind
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:19450-19466
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Data-SUITE: Data-centric identification of in-distribution incongruous examples
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:19467-19496
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Continuous-Time Modeling of Counterfactual Outcomes Using Neural Controlled Differential Equations
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:19497-19521
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Neural Tangent Kernel Beyond the Infinite-Width Limit: Effects of Depth and Initialization
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:19522-19560
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Reinforcement Learning with Action-Free Pre-Training from Videos
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:19561-19579
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Efficient Model-based Multi-agent Reinforcement Learning via Optimistic Equilibrium Computation
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:19580-19597
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Selective Regression under Fairness Criteria
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:19598-19615
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Utility Theory for Sequential Decision Making
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:19616-19625
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Translating Robot Skills: Learning Unsupervised Skill Correspondences Across Robots
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:19626-19644
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A State-Distribution Matching Approach to Non-Episodic Reinforcement Learning
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:19645-19657
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Content Addressable Memory Without Catastrophic Forgetting by Heteroassociation with a Fixed Scaffold
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:19658-19682
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Federated Minimax Optimization: Improved Convergence Analyses and Algorithms
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:19683-19730
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DNS: Determinantal Point Process Based Neural Network Sampler for Ensemble Reinforcement Learning
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:19731-19746
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Instance Dependent Regret Analysis of Kernelized Bandits
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:19747-19772
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Data Augmentation as Feature Manipulation
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:19773-19808
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Metric-Fair Active Learning
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:19809-19826
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PDO-s3DCNNs: Partial Differential Operator Based Steerable 3D CNNs
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:19827-19846
Connect, Not Collapse: Explaining Contrastive Learning for Unsupervised Domain Adaptation
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:19847-19878
Constrained Optimization with Dynamic Bound-scaling for Effective NLP Backdoor Defense
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:19879-19892
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Staged Training for Transformer Language Models
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:19893-19908
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Deep Network Approximation in Terms of Intrinsic Parameters
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:19909-19934
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Gradient-Free Method for Heavily Constrained Nonconvex Optimization
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:19935-19955
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Global Optimization of K-Center Clustering
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:19956-19966
Pessimistic Q-Learning for Offline Reinforcement Learning: Towards Optimal Sample Complexity
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:19967-20025
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Adversarial Masking for Self-Supervised Learning
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:20026-20040
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Visual Attention Emerges from Recurrent Sparse Reconstruction
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:20041-20056
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A Minimax Learning Approach to Off-Policy Evaluation in Confounded Partially Observable Markov Decision Processes
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:20057-20094
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Robust Group Synchronization via Quadratic Programming
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:20095-20105
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Log-Euclidean Signatures for Intrinsic Distances Between Unaligned Datasets
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:20106-20124
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Scalable Computation of Causal Bounds
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:20125-20140
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Bit Prioritization in Variational Autoencoders via Progressive Coding
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:20141-20155
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Fair Representation Learning through Implicit Path Alignment
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:20156-20175
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Faster Algorithms for Learning Convex Functions
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:20176-20194
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Coin Flipping Neural Networks
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:20195-20214
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Reverse Engineering the Neural Tangent Kernel
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:20215-20231
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Demystifying the Adversarial Robustness of Random Transformation Defenses
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:20232-20252
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Smoothed Adversarial Linear Contextual Bandits with Knapsacks
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:20253-20277
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GenLabel: Mixup Relabeling using Generative Models
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:20278-20313
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Communicating via Markov Decision Processes
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:20314-20328
The Multivariate Community Hawkes Model for Dependent Relational Events in Continuous-time Networks
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:20329-20346
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Disentangling Sources of Risk for Distributional Multi-Agent Reinforcement Learning
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:20347-20368
TAM: Topology-Aware Margin Loss for Class-Imbalanced Node Classification
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:20369-20383
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A General Recipe for Likelihood-free Bayesian Optimization
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:20384-20404
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Fully-Connected Network on Noncompact Symmetric Space and Ridgelet Transform based on Helgason-Fourier Analysis
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:20405-20422
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Saute RL: Almost Surely Safe Reinforcement Learning Using State Augmentation
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:20423-20443
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Lightweight Projective Derivative Codes for Compressed Asynchronous Gradient Descent
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:20444-20458
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Accelerating Bayesian Optimization for Biological Sequence Design with Denoising Autoencoders
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:20459-20478
3D Infomax improves GNNs for Molecular Property Prediction
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:20479-20502
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EquiBind: Geometric Deep Learning for Drug Binding Structure Prediction
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:20503-20521
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Plug & Play Attacks: Towards Robust and Flexible Model Inversion Attacks
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:20522-20545
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Scaling-up Diverse Orthogonal Convolutional Networks by a Paraunitary Framework
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:20546-20579
Divergence-Regularized Multi-Agent Actor-Critic
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:20580-20603
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Influence-Augmented Local Simulators: a Scalable Solution for Fast Deep RL in Large Networked Systems
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:20604-20624
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Improved StyleGAN-v2 based Inversion for Out-of-Distribution Images
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:20625-20639
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Continuous-Time Analysis of Accelerated Gradient Methods via Conservation Laws in Dilated Coordinate Systems
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:20640-20667
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Do Differentiable Simulators Give Better Policy Gradients?
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:20668-20696
Intriguing Properties of Input-Dependent Randomized Smoothing
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:20697-20743
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Cliff Diving: Exploring Reward Surfaces in Reinforcement Learning Environments
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:20744-20776
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AGNAS: Attention-Guided Micro and Macro-Architecture Search
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:20777-20789
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Adaptive Random Walk Gradient Descent for Decentralized Optimization
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:20790-20809
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MAE-DET: Revisiting Maximum Entropy Principle in Zero-Shot NAS for Efficient Object Detection
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:20810-20826
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Out-of-Distribution Detection with Deep Nearest Neighbors
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:20827-20840
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Black-Box Tuning for Language-Model-as-a-Service
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:20841-20855
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Correlated Quantization for Distributed Mean Estimation and Optimization
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:20856-20876
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Causal Imitation Learning under Temporally Correlated Noise
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:20877-20890
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Being Properly Improper
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:20891-20932
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Distributionally-Aware Kernelized Bandit Problems for Risk Aversion
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:20933-20959
Sequential and Parallel Constrained Max-value Entropy Search via Information Lower Bound
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:20960-20986
SQ-VAE: Variational Bayes on Discrete Representation with Self-annealed Stochastic Quantization
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:20987-21012
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A Tree-based Model Averaging Approach for Personalized Treatment Effect Estimation from Heterogeneous Data Sources
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:21013-21036
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N-Penetrate: Active Learning of Neural Collision Handler for Complex 3D Mesh Deformations
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:21037-21049
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Biased Gradient Estimate with Drastic Variance Reduction for Meta Reinforcement Learning
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:21050-21075
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Rethinking Graph Neural Networks for Anomaly Detection
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:21076-21089
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Deep Safe Incomplete Multi-view Clustering: Theorem and Algorithm
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:21090-21110
Virtual Homogeneity Learning: Defending against Data Heterogeneity in Federated Learning
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:21111-21132
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Cross-Space Active Learning on Graph Convolutional Networks
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:21133-21145
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FedNest: Federated Bilevel, Minimax, and Compositional Optimization
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:21146-21179
Efficient Distributionally Robust Bayesian Optimization with Worst-case Sensitivity
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:21180-21204
LIDL: Local Intrinsic Dimension Estimation Using Approximate Likelihood
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:21205-21231
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LCANets: Lateral Competition Improves Robustness Against Corruption and Attack
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:21232-21252
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Reverse Engineering $\ell_p$ attacks: A block-sparse optimization approach with recovery guarantees
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:21253-21271
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Generalised Policy Improvement with Geometric Policy Composition
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:21272-21307
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Algorithms for the Communication of Samples
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:21308-21328
Consistent Polyhedral Surrogates for Top-k Classification and Variants
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:21329-21359
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On the Finite-Time Complexity and Practical Computation of Approximate Stationarity Concepts of Lipschitz Functions
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:21360-21379
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From Dirichlet to Rubin: Optimistic Exploration in RL without Bonuses
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:21380-21431
Nonparametric Sparse Tensor Factorization with Hierarchical Gamma Processes
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:21432-21448
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Deciphering Lasso-based Classification Through a Large Dimensional Analysis of the Iterative Soft-Thresholding Algorithm
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:21449-21477
Extended Unconstrained Features Model for Exploring Deep Neural Collapse
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:21478-21505
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Object Permanence Emerges in a Random Walk along Memory
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:21506-21519
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Generic Coreset for Scalable Learning of Monotonic Kernels: Logistic Regression, Sigmoid and more
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:21520-21547
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Failure and success of the spectral bias prediction for Laplace Kernel Ridge Regression: the case of low-dimensional data
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:21548-21583
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Quantifying and Learning Linear Symmetry-Based Disentanglement
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:21584-21608
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A Temporal-Difference Approach to Policy Gradient Estimation
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:21609-21632
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Simple and near-optimal algorithms for hidden stratification and multi-group learning
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:21633-21657
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Design-Bench: Benchmarks for Data-Driven Offline Model-Based Optimization
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:21658-21676
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AnyMorph: Learning Transferable Polices By Inferring Agent Morphology
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:21677-21691
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Detecting Adversarial Examples Is (Nearly) As Hard As Classifying Them
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:21692-21702
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Nesterov Accelerated Shuffling Gradient Method for Convex Optimization
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:21703-21732
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A Completely Tuning-Free and Robust Approach to Sparse Precision Matrix Estimation
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:21733-21750
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Tackling covariate shift with node-based Bayesian neural networks
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:21751-21775
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Fenrir: Physics-Enhanced Regression for Initial Value Problems
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:21776-21794
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Interpretable Off-Policy Learning via Hyperbox Search
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:21795-21827
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FriendlyCore: Practical Differentially Private Aggregation
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:21828-21863
Pairwise Conditional Gradients without Swap Steps and Sparser Kernel Herding
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:21864-21883
Prototype Based Classification from Hierarchy to Fairness
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:21884-21900
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Consensus Multiplicative Weights Update: Learning to Learn using Projector-based Game Signatures
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:21901-21926
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Self-Supervised Models of Audio Effectively Explain Human Cortical Responses to Speech
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:21927-21944
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Path-Gradient Estimators for Continuous Normalizing Flows
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:21945-21959
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Improved Convergence Rates for Sparse Approximation Methods in Kernel-Based Learning
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:21960-21983
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EDEN: Communication-Efficient and Robust Distributed Mean Estimation for Federated Learning
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:21984-22014
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Towards Noise-adaptive, Problem-adaptive (Accelerated) Stochastic Gradient Descent
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:22015-22059
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Correlation Clustering via Strong Triadic Closure Labeling: Fast Approximation Algorithms and Practical Lower Bounds
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:22060-22083
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The CLRS Algorithmic Reasoning Benchmark
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:22084-22102
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Bregman Power k-Means for Clustering Exponential Family Data
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:22103-22119
Estimation in Rotationally Invariant Generalized Linear Models via Approximate Message Passing
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:22120-22144
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Bayesian Optimization under Stochastic Delayed Feedback
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:22145-22167
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VarScene: A Deep Generative Model for Realistic Scene Graph Synthesis
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:22168-22183
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Calibrated Learning to Defer with One-vs-All Classifiers
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:22184-22202
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Regret Bounds for Stochastic Shortest Path Problems with Linear Function Approximation
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:22203-22233
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On Implicit Bias in Overparameterized Bilevel Optimization
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:22234-22259
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Multiclass learning with margin: exponential rates with no bias-variance trade-off
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:22260-22269
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Addressing Optimism Bias in Sequence Modeling for Reinforcement Learning
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:22270-22283
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Bayesian Nonparametrics for Offline Skill Discovery
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:22284-22299
Hermite Polynomial Features for Private Data Generation
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:22300-22324
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What Can Linear Interpolation of Neural Network Loss Landscapes Tell Us?
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:22325-22341
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Multirate Training of Neural Networks
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:22342-22360
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Provably Adversarially Robust Nearest Prototype Classifiers
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:22361-22383
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First-Order Regret in Reinforcement Learning with Linear Function Approximation: A Robust Estimation Approach
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:22384-22429
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Reward-Free RL is No Harder Than Reward-Aware RL in Linear Markov Decision Processes
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:22430-22456
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Training Characteristic Functions with Reinforcement Learning: XAI-methods play Connect Four
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:22457-22474
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Retroformer: Pushing the Limits of End-to-end Retrosynthesis Transformer
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:22475-22490
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Safe Exploration for Efficient Policy Evaluation and Comparison
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:22491-22511
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Greedy based Value Representation for Optimal Coordination in Multi-agent Reinforcement Learning
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:22512-22535
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Towards Evaluating Adaptivity of Model-Based Reinforcement Learning Methods
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:22536-22561
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Fast Lossless Neural Compression with Integer-Only Discrete Flows
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:22562-22575
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Accelerating Shapley Explanation via Contributive Cooperator Selection
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:22576-22590
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Denoised MDPs: Learning World Models Better Than the World Itself
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:22591-22612
Neural Implicit Dictionary Learning via Mixture-of-Expert Training
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:22613-22624
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Robust Models Are More Interpretable Because Attributions Look Normal
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:22625-22651
Disentangling Disease-related Representation from Obscure for Disease Prediction
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:22652-22664
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Solving Stackelberg Prediction Game with Least Squares Loss via Spherically Constrained Least Squares Reformulation
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:22665-22679
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VLMixer: Unpaired Vision-Language Pre-training via Cross-Modal CutMix
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:22680-22690
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DynaMixer: A Vision MLP Architecture with Dynamic Mixing
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:22691-22701
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Improving Screening Processes via Calibrated Subset Selection
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:22702-22726
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The Geometry of Robust Value Functions
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:22727-22751
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What Dense Graph Do You Need for Self-Attention?
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:22752-22768
Improved Certified Defenses against Data Poisoning with (Deterministic) Finite Aggregation
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:22769-22783
Understanding Gradual Domain Adaptation: Improved Analysis, Optimal Path and Beyond
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:22784-22801
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Communication-Efficient Adaptive Federated Learning
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:22802-22838
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Provable Acceleration of Heavy Ball beyond Quadratics for a Class of Polyak-Lojasiewicz Functions when the Non-Convexity is Averaged-Out
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:22839-22864
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Robustness Verification for Contrastive Learning
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:22865-22883
Convergence and Recovery Guarantees of the K-Subspaces Method for Subspace Clustering
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:22884-22918
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NP-Match: When Neural Processes meet Semi-Supervised Learning
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:22919-22934
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Iterative Double Sketching for Faster Least-Squares Optimization
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:22935-22963
What Language Model Architecture and Pretraining Objective Works Best for Zero-Shot Generalization?
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:22964-22984
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Improving Task-free Continual Learning by Distributionally Robust Memory Evolution
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:22985-22998
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Risk-Averse No-Regret Learning in Online Convex Games
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:22999-23017
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Provable Domain Generalization via Invariant-Feature Subspace Recovery
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:23018-23033
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ProgFed: Effective, Communication, and Computation Efficient Federated Learning by Progressive Training
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:23034-23054
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Model-based Meta Reinforcement Learning using Graph Structured Surrogate Models and Amortized Policy Search
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:23055-23077
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Approximately Equivariant Networks for Imperfectly Symmetric Dynamics
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:23078-23091
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Three-stage Evolution and Fast Equilibrium for SGD with Non-degerate Critical Points
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:23092-23113
Understanding Instance-Level Impact of Fairness Constraints
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:23114-23130
Tractable Uncertainty for Structure Learning
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:23131-23150
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Causal Dynamics Learning for Task-Independent State Abstraction
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:23151-23180
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Multiple-Play Stochastic Bandits with Shareable Finite-Capacity Arms
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:23181-23212
Generative Coarse-Graining of Molecular Conformations
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:23213-23236
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Nonparametric Embeddings of Sparse High-Order Interaction Events
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:23237-23253
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When Are Linear Stochastic Bandits Attackable?
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:23254-23273
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DRAGONN: Distributed Randomized Approximate Gradients of Neural Networks
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:23274-23291
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Finite-Sum Coupled Compositional Stochastic Optimization: Theory and Applications
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:23292-23317
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OFA: Unifying Architectures, Tasks, and Modalities Through a Simple Sequence-to-Sequence Learning Framework
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:23318-23340
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How Powerful are Spectral Graph Neural Networks
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:23341-23362
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Thompson Sampling for Robust Transfer in Multi-Task Bandits
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:23363-23416
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Individual Reward Assisted Multi-Agent Reinforcement Learning
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:23417-23432
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Removing Batch Normalization Boosts Adversarial Training
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:23433-23445
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Partial and Asymmetric Contrastive Learning for Out-of-Distribution Detection in Long-Tailed Recognition
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:23446-23458
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Nonparametric Factor Trajectory Learning for Dynamic Tensor Decomposition
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:23459-23469
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Thompson Sampling for (Combinatorial) Pure Exploration
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:23470-23483
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Policy Gradient Method For Robust Reinforcement Learning
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:23484-23526
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Certifying Out-of-Domain Generalization for Blackbox Functions
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:23527-23548
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More Than a Toy: Random Matrix Models Predict How Real-World Neural Representations Generalize
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:23549-23588
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To Smooth or Not? When Label Smoothing Meets Noisy Labels
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:23589-23614
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Open-Sampling: Exploring Out-of-Distribution data for Re-balancing Long-tailed datasets
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:23615-23630
Mitigating Neural Network Overconfidence with Logit Normalization
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:23631-23644
Koopman Q-learning: Offline Reinforcement Learning via Symmetries of Dynamics
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:23645-23667
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Fishing for User Data in Large-Batch Federated Learning via Gradient Magnification
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:23668-23684
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BabelTower: Learning to Auto-parallelized Program Translation
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:23685-23700
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Random Forest Density Estimation
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:23701-23722
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Fighting Fire with Fire: Avoiding DNN Shortcuts through Priming
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:23723-23750
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Preconditioning for Scalable Gaussian Process Hyperparameter Optimization
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:23751-23780
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Measure Estimation in the Barycentric Coding Model
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:23781-23803
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COLA: Consistent Learning with Opponent-Learning Awareness
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:23804-23831
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Distributional Hamilton-Jacobi-Bellman Equations for Continuous-Time Reinforcement Learning
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:23832-23856
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Easy Variational Inference for Categorical Models via an Independent Binary Approximation
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:23857-23896
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Continual Learning with Guarantees via Weight Interval Constraints
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:23897-23911
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A Deep Learning Approach for the Segmentation of Electroencephalography Data in Eye Tracking Applications
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:23912-23932
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Leverage Score Sampling for Tensor Product Matrices in Input Sparsity Time
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:23933-23964
Model soups: averaging weights of multiple fine-tuned models improves accuracy without increasing inference time
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:23965-23998
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Metric-Fair Classifier Derandomization
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:23999-24016
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Structural Entropy Guided Graph Hierarchical Pooling
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:24017-24030
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Self-supervised Models are Good Teaching Assistants for Vision Transformers
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:24031-24042
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Characterizing and Overcoming the Greedy Nature of Learning in Multi-modal Deep Neural Networks
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:24043-24055
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Instrumental Variable Regression with Confounder Balancing
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:24056-24075
MemSR: Training Memory-efficient Lightweight Model for Image Super-Resolution
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:24076-24092
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Delay-Adaptive Step-sizes for Asynchronous Learning
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:24093-24113
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Variational nearest neighbor Gaussian process
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:24114-24130
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Understanding Policy Gradient Algorithms: A Sensitivity-Based Approach
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:24131-24149
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DAVINZ: Data Valuation using Deep Neural Networks at Initialization
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:24150-24176
Robust Deep Reinforcement Learning through Bootstrapped Opportunistic Curriculum
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:24177-24211
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Revisiting Consistency Regularization for Deep Partial Label Learning
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:24212-24225
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Flowformer: Linearizing Transformers with Conservation Flows
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:24226-24242
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Nearly Optimal Policy Optimization with Stable at Any Time Guarantee
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:24243-24265
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RetrievalGuard: Provably Robust 1-Nearest Neighbor Image Retrieval
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:24266-24279
Last Iterate Risk Bounds of SGD with Decaying Stepsize for Overparameterized Linear Regression
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:24280-24314
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Optimal Clustering with Noisy Queries via Multi-Armed Bandit
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:24315-24331
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ProGCL: Rethinking Hard Negative Mining in Graph Contrastive Learning
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:24332-24346
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Synergy and Symmetry in Deep Learning: Interactions between the Data, Model, and Inference Algorithm
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:24347-24369
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Identification of Linear Non-Gaussian Latent Hierarchical Structure
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:24370-24387
COAT: Measuring Object Compositionality in Emergent Representations
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:24388-24413
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Robust Policy Learning over Multiple Uncertainty Sets
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:24414-24429
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Adaptive Inertia: Disentangling the Effects of Adaptive Learning Rate and Momentum
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:24430-24459
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Self-Supervised Representation Learning via Latent Graph Prediction
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:24460-24477
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Efficient Computation of Higher-Order Subgraph Attribution via Message Passing
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:24478-24495
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A Self-Play Posterior Sampling Algorithm for Zero-Sum Markov Games
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:24496-24523
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Importance Weighted Kernel Bayes’ Rule
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:24524-24538
Learning to Separate Voices by Spatial Regions
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:24539-24549
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Detached Error Feedback for Distributed SGD with Random Sparsification
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:24550-24575
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Accurate Quantization of Measures via Interacting Particle-based Optimization
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:24576-24595
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Unified Fourier-based Kernel and Nonlinearity Design for Equivariant Networks on Homogeneous Spaces
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:24596-24614
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Inferring Cause and Effect in the Presence of Heteroscedastic Noise
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:24615-24630
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Prompting Decision Transformer for Few-Shot Policy Generalization
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:24631-24645
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Analyzing and Mitigating Interference in Neural Architecture Search
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:24646-24662
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On the Statistical Benefits of Curriculum Learning
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:24663-24682
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A Difference Standardization Method for Mutual Transfer Learning
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:24683-24697
SkexGen: Autoregressive Generation of CAD Construction Sequences with Disentangled Codebooks
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:24698-24724
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Discriminator-Weighted Offline Imitation Learning from Suboptimal Demonstrations
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:24725-24742
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Adversarial Attack and Defense for Non-Parametric Two-Sample Tests
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:24743-24769
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Adversarially Robust Models may not Transfer Better: Sufficient Conditions for Domain Transferability from the View of Regularization
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:24770-24802
A Theoretical Analysis on Independence-driven Importance Weighting for Covariate-shift Generalization
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:24803-24829
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Langevin Monte Carlo for Contextual Bandits
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:24830-24850
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Investigating Why Contrastive Learning Benefits Robustness against Label Noise
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:24851-24871
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Diversified Adversarial Attacks based on Conjugate Gradient Method
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:24872-24894
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Cycle Representation Learning for Inductive Relation Prediction
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:24895-24910
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Optimally Controllable Perceptual Lossy Compression
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:24911-24928
Active fairness auditing
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:24929-24962
Self-Organized Polynomial-Time Coordination Graphs
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:24963-24979
Regularizing a Model-based Policy Stationary Distribution to Stabilize Offline Reinforcement Learning
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:24980-25006
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A Psychological Theory of Explainability
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:25007-25021
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Omni-Granular Ego-Semantic Propagation for Self-Supervised Graph Representation Learning
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:25022-25037
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Unsupervised Time-Series Representation Learning with Iterative Bilinear Temporal-Spectral Fusion
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:25038-25054
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Searching for BurgerFormer with Micro-Meso-Macro Space Design
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:25055-25069
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Efficient Variance Reduction for Meta-learning
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:25070-25095
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Injecting Logical Constraints into Neural Networks via Straight-Through Estimators
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:25096-25122
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Locally Sparse Neural Networks for Tabular Biomedical Data
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:25123-25153
Not All Poisons are Created Equal: Robust Training against Data Poisoning
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:25154-25165
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Does the Data Induce Capacity Control in Deep Learning?
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:25166-25197
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Informed Learning by Wide Neural Networks: Convergence, Generalization and Sampling Complexity
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:25198-25240
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Linear Bandit Algorithms with Sublinear Time Complexity
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:25241-25260
A New Perspective on the Effects of Spectrum in Graph Neural Networks
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:25261-25279
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Fourier Learning with Cyclical Data
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:25280-25301
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Estimating Instance-dependent Bayes-label Transition Matrix using a Deep Neural Network
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:25302-25312
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A Study of Face Obfuscation in ImageNet
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:25313-25330
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Anarchic Federated Learning
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:25331-25363
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Identity-Disentangled Adversarial Augmentation for Self-supervised Learning
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:25364-25381
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Learning from a Learning User for Optimal Recommendations
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:25382-25406
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Improving Out-of-Distribution Robustness via Selective Augmentation
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:25407-25437
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NLP From Scratch Without Large-Scale Pretraining: A Simple and Efficient Framework
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:25438-25451
Feature Space Particle Inference for Neural Network Ensembles
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:25452-25468
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Centroid Approximation for Bootstrap: Improving Particle Quality at Inference
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:25469-25489
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Be Like Water: Adaptive Floating Point for Machine Learning
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:25490-25500
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QSFL: A Two-Level Uplink Communication Optimization Framework for Federated Learning
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:25501-25513
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De novo mass spectrometry peptide sequencing with a transformer model
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:25514-25522
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Bayesian Nonparametric Learning for Point Processes with Spatial Homogeneity: A Spatial Analysis of NBA Shot Locations
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:25523-25551
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Bitwidth Heterogeneous Federated Learning with Progressive Weight Dequantization
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:25552-25565
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ShiftAddNAS: Hardware-Inspired Search for More Accurate and Efficient Neural Networks
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:25566-25580
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Molecular Representation Learning via Heterogeneous Motif Graph Neural Networks
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:25581-25594
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Understanding Robust Overfitting of Adversarial Training and Beyond
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:25595-25610
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How to Leverage Unlabeled Data in Offline Reinforcement Learning
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:25611-25635
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Reachability Constrained Reinforcement Learning
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:25636-25655
Topology-Aware Network Pruning using Multi-stage Graph Embedding and Reinforcement Learning
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:25656-25667
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The Combinatorial Brain Surgeon: Pruning Weights That Cancel One Another in Neural Networks
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:25668-25683
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GraphFM: Improving Large-Scale GNN Training via Feature Momentum
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:25684-25701
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Latent Diffusion Energy-Based Model for Interpretable Text Modelling
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:25702-25720
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Predicting Out-of-Distribution Error with the Projection Norm
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:25721-25746
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Robust Task Representations for Offline Meta-Reinforcement Learning via Contrastive Learning
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:25747-25759
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Provable Stochastic Optimization for Global Contrastive Learning: Small Batch Does Not Harm Performance
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:25760-25782
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Neural Tangent Kernel Empowered Federated Learning
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:25783-25803
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Time Is MattEr: Temporal Self-supervision for Video Transformers
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:25804-25816
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Pure Noise to the Rescue of Insufficient Data: Improving Imbalanced Classification by Training on Random Noise Images
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:25817-25833
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Adaptive Conformal Predictions for Time Series
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:25834-25866
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Actor-Critic based Improper Reinforcement Learning
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:25867-25919
Stabilizing Q-learning with Linear Architectures for Provable Efficient Learning
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:25920-25954
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Multi Resolution Analysis (MRA) for Approximate Self-Attention
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:25955-25972
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Efficient PAC Learning from the Crowd with Pairwise Comparisons
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:25973-25993
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Multi-Grained Vision Language Pre-Training: Aligning Texts with Visual Concepts
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:25994-26009
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Position Prediction as an Effective Pretraining Strategy
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:26010-26027
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Anytime Information Cascade Popularity Prediction via Self-Exciting Processes
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:26028-26047
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Understanding Clipping for Federated Learning: Convergence and Client-Level Differential Privacy
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:26048-26067
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Collaboration of Experts: Achieving 80% Top-1 Accuracy on ImageNet with 100M FLOPs
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:26068-26084
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PDE-Based Optimal Strategy for Unconstrained Online Learning
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:26085-26115
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Stochastic Continuous Submodular Maximization: Boosting via Non-oblivious Function
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:26116-26134
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When and How Mixup Improves Calibration
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:26135-26160
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UAST: Uncertainty-Aware Siamese Tracking
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:26161-26175
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Examining Scaling and Transfer of Language Model Architectures for Machine Translation
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:26176-26192
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Revisiting End-to-End Speech-to-Text Translation From Scratch
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:26193-26205
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A Stochastic Multi-Rate Control Framework For Modeling Distributed Optimization Algorithms
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:26206-26222
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GALAXY: Graph-based Active Learning at the Extreme
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:26223-26238
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Fairness Interventions as (Dis)Incentives for Strategic Manipulation
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:26239-26264
Role-based Multiplex Network Embedding
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:26265-26280
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Dynamic Topic Models for Temporal Document Networks
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:26281-26292
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Personalized Federated Learning via Variational Bayesian Inference
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:26293-26310
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Federated Learning with Label Distribution Skew via Logits Calibration
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:26311-26329
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Neural Network Weights Do Not Converge to Stationary Points: An Invariant Measure Perspective
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:26330-26346
Beyond Worst-Case Analysis in Stochastic Approximation: Moment Estimation Improves Instance Complexity
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:26347-26361
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Deep and Flexible Graph Neural Architecture Search
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:26362-26374
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A Langevin-like Sampler for Discrete Distributions
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:26375-26396
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Rich Feature Construction for the Optimization-Generalization Dilemma
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:26397-26411
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Generative Flow Networks for Discrete Probabilistic Modeling
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:26412-26428
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Neurotoxin: Durable Backdoors in Federated Learning
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:26429-26446
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Making Linear MDPs Practical via Contrastive Representation Learning
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:26447-26466
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NAFS: A Simple yet Tough-to-beat Baseline for Graph Representation Learning
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:26467-26483
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Correct-N-Contrast: a Contrastive Approach for Improving Robustness to Spurious Correlations
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:26484-26516
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Efficient Reinforcement Learning in Block MDPs: A Model-free Representation Learning approach
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:26517-26547
Partial Counterfactual Identification from Observational and Experimental Data
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:26548-26558
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Set Norm and Equivariant Skip Connections: Putting the Deep in Deep Sets
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:26559-26574
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Learning to Estimate and Refine Fluid Motion with Physical Dynamics
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:26575-26590
A Branch and Bound Framework for Stronger Adversarial Attacks of ReLU Networks
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:26591-26604
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A Simple yet Universal Strategy for Online Convex Optimization
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:26605-26623
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Low-Precision Stochastic Gradient Langevin Dynamics
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:26624-26644
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Expression might be enough: representing pressure and demand for reinforcement learning based traffic signal control
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:26645-26654
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Uncertainty Modeling in Generative Compressed Sensing
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:26655-26668
Building Robust Ensembles via Margin Boosting
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:26669-26692
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Revisiting and Advancing Fast Adversarial Training Through The Lens of Bi-Level Optimization
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:26693-26712
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Off-Policy Fitted Q-Evaluation with Differentiable Function Approximators: Z-Estimation and Inference Theory
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:26713-26749
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ROCK: Causal Inference Principles for Reasoning about Commonsense Causality
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:26750-26771
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No-Regret Learning in Time-Varying Zero-Sum Games
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:26772-26808
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PLATON: Pruning Large Transformer Models with Upper Confidence Bound of Weight Importance
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:26809-26823
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NysADMM: faster composite convex optimization via low-rank approximation
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:26824-26840
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Toward Compositional Generalization in Object-Oriented World Modeling
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:26841-26864
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Dynamic Regret of Online Markov Decision Processes
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:26865-26894
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Learning to Solve PDE-constrained Inverse Problems with Graph Networks
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:26895-26910
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Learning from Counterfactual Links for Link Prediction
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:26911-26926
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Global Optimization Networks
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:26927-26957
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Certified Robustness Against Natural Language Attacks by Causal Intervention
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:26958-26970
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Efficient Learning for AlphaZero via Path Consistency
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:26971-26981
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Penalizing Gradient Norm for Efficiently Improving Generalization in Deep Learning
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:26982-26992
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Ripple Attention for Visual Perception with Sub-quadratic Complexity
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:26993-27010
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Linear Complexity Randomized Self-attention Mechanism
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:27011-27041
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Online Decision Transformer
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:27042-27059
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Learning Efficient and Robust Ordinary Differential Equations via Invertible Neural Networks
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:27060-27074
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HyperTransformer: Model Generation for Supervised and Semi-Supervised Few-Shot Learning
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:27075-27098
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Describing Differences between Text Distributions with Natural Language
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:27099-27116
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Pessimistic Minimax Value Iteration: Provably Efficient Equilibrium Learning from Offline Datasets
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:27117-27142
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Dimension-free Complexity Bounds for High-order Nonconvex Finite-sum Optimization
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:27143-27158
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A Hierarchical Bayesian Approach to Inverse Reinforcement Learning with Symbolic Reward Machines
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:27159-27178
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On the Optimization Landscape of Neural Collapse under MSE Loss: Global Optimality with Unconstrained Features
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:27179-27202
Model Agnostic Sample Reweighting for Out-of-Distribution Learning
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:27203-27221
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Sparse Invariant Risk Minimization
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:27222-27244
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Prototype-Anchored Learning for Learning with Imperfect Annotations
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:27245-27267
FEDformer: Frequency Enhanced Decomposed Transformer for Long-term Series Forecasting
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:27268-27286
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Probabilistic Bilevel Coreset Selection
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:27287-27302
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Approximate Frank-Wolfe Algorithms over Graph-structured Support Sets
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:27303-27337
Improving Adversarial Robustness via Mutual Information Estimation
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:27338-27352
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Modeling Adversarial Noise for Adversarial Training
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:27353-27366
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Contrastive Learning with Boosted Memorization
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:27367-27377
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Understanding The Robustness in Vision Transformers
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:27378-27394
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VLUE: A Multi-Task Multi-Dimension Benchmark for Evaluating Vision-Language Pre-training
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:27395-27411
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Detecting Corrupted Labels Without Training a Model to Predict
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:27412-27427
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Contextual Bandits with Large Action Spaces: Made Practical
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:27428-27453
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Neural-Symbolic Models for Logical Queries on Knowledge Graphs
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:27454-27478
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Topology-aware Generalization of Decentralized SGD
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:27479-27503
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Resilient and Communication Efficient Learning for Heterogeneous Federated Systems
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:27504-27526
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On Numerical Integration in Neural Ordinary Differential Equations
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:27527-27547
When AUC meets DRO: Optimizing Partial AUC for Deep Learning with Non-Convex Convergence Guarantee
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:27548-27573
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Contextual Bandits with Smooth Regret: Efficient Learning in Continuous Action Spaces
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:27574-27590
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Residual-Based Sampling for Online Outlier-Robust PCA
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:27591-27611
Region-Based Semantic Factorization in GANs
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:27612-27632
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Beyond Images: Label Noise Transition Matrix Estimation for Tasks with Lower-Quality Features
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:27633-27653
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Towards Uniformly Superhuman Autonomy via Subdominance Minimization
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:27654-27670
Inductive Matrix Completion: No Bad Local Minima and a Fast Algorithm
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:27671-27692
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Counterfactual Prediction for Outcome-Oriented Treatments
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:27693-27706
SpaceMAP: Visualizing High-Dimensional Data by Space Expansion
; Proceedings of the 39th International Conference on Machine Learning, PMLR 162:27707-27723
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