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Volume 119: International Conference on Machine Learning, 13-18 July 2020, Virtual
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Editors: Hal Daumé III, Aarti Singh
Selective Dyna-Style Planning Under Limited Model Capacity
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:1-10
A distributional view on multi-objective policy optimization
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:11-22
Efficient Optimistic Exploration in Linear-Quadratic Regulators via Lagrangian Relaxation
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:23-31
Super-efficiency of automatic differentiation for functions defined as a minimum
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:32-41
A Geometric Approach to Archetypal Analysis via Sparse Projections
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:42-51
Context Aware Local Differential Privacy
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:52-62
Efficient Intervention Design for Causal Discovery with Latents
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:63-73
The Neural Tangent Kernel in High Dimensions: Triple Descent and a Multi-Scale Theory of Generalization
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:74-84
Rank Aggregation from Pairwise Comparisons in the Presence of Adversarial Corruptions
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:85-95
Boosting for Control of Dynamical Systems
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:96-103
An Optimistic Perspective on Offline Reinforcement Learning
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:104-114
Optimal Bounds between f-Divergences and Integral Probability Metrics
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:115-124
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LazyIter: A Fast Algorithm for Counting Markov Equivalent DAGs and Designing Experiments
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:125-133
Learning What to Defer for Maximum Independent Sets
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:134-144
Invariant Risk Minimization Games
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:145-155
Why bigger is not always better: on finite and infinite neural networks
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:156-164
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Discriminative Jackknife: Quantifying Uncertainty in Deep Learning via Higher-Order Influence Functions
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:165-174
Frequentist Uncertainty in Recurrent Neural Networks via Blockwise Influence Functions
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:175-190
Random extrapolation for primal-dual coordinate descent
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:191-201
A new regret analysis for Adam-type algorithms
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:202-210
Restarted Bayesian Online Change-point Detector achieves Optimal Detection Delay
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:211-221
Maximum Likelihood with Bias-Corrected Calibration is Hard-To-Beat at Label Shift Adaptation
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:222-232
The Implicit Regularization of Stochastic Gradient Flow for Least Squares
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:233-244
Structural Language Models of Code
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:245-256
LowFER: Low-rank Bilinear Pooling for Link Prediction
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:257-268
Discount Factor as a Regularizer in Reinforcement Learning
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:269-278
Neuro-Symbolic Visual Reasoning: Disentangling "Visual" from "Reasoning"
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:279-290
The Differentiable Cross-Entropy Method
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:291-302
Customizing ML Predictions for Online Algorithms
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:303-313
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Fairwashing explanations with off-manifold detergent
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:314-323
Population-Based Black-Box Optimization for Biological Sequence Design
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:324-334
Low-loss connection of weight vectors: distribution-based approaches
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:335-344
Online metric algorithms with untrusted predictions
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:345-355
NADS: Neural Architecture Distribution Search for Uncertainty Awareness
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:356-366
Provable Representation Learning for Imitation Learning via Bi-level Optimization
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:367-376
Quantum Boosting
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:377-387
Black-box Certification and Learning under Adversarial Perturbations
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:388-398
Invertible generative models for inverse problems: mitigating representation error and dataset bias
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:399-409
On the Convergence of Nesterov’s Accelerated Gradient Method in Stochastic Settings
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:410-420
Safe screening rules for L0-regression from Perspective Relaxations
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:421-430
Adversarial Learning Guarantees for Linear Hypotheses and Neural Networks
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:431-441
Sample Amplification: Increasing Dataset Size even when Learning is Impossible
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:442-451
Sparse Convex Optimization via Adaptively Regularized Hard Thresholding
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:452-462
Model-Based Reinforcement Learning with Value-Targeted Regression
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:463-474
Forecasting Sequential Data Using Consistent Koopman Autoencoders
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:475-485
Constant Curvature Graph Convolutional Networks
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:486-496
Scalable Nearest Neighbor Search for Optimal Transport
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:497-506
Agent57: Outperforming the Atari Human Benchmark
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:507-517
Fiduciary Bandits
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:518-527
Learning De-biased Representations with Biased Representations
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:528-539
Deep k-NN for Noisy Labels
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:540-550
Provable Self-Play Algorithms for Competitive Reinforcement Learning
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:551-560
Sparse Subspace Clustering with Entropy-Norm
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:561-568
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Coresets for Clustering in Graphs of Bounded Treewidth
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:569-579
Refined bounds for algorithm configuration: The knife-edge of dual class approximability
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:580-590
Ready Policy One: World Building Through Active Learning
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:591-601
Stochastic Optimization for Regularized Wasserstein Estimators
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:602-612
Dual Mirror Descent for Online Allocation Problems
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:613-628
Inductive-bias-driven Reinforcement Learning For Efficient Schedules in Heterogeneous Clusters
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:629-641
UniLMv2: Pseudo-Masked Language Models for Unified Language Model Pre-Training
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:642-652
Fast OSCAR and OWL Regression via Safe Screening Rules
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:653-663
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Option Discovery in the Absence of Rewards with Manifold Analysis
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:664-674
Learning the piece-wise constant graph structure of a varying Ising model
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:675-684
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Frequency Bias in Neural Networks for Input of Non-Uniform Density
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:685-694
Private Query Release Assisted by Public Data
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:695-703
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ECLIPSE: An Extreme-Scale Linear Program Solver for Web-Applications
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:704-714
On Second-Order Group Influence Functions for Black-Box Predictions
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:715-724
Kernel interpolation with continuous volume sampling
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:725-735
Decoupled Greedy Learning of CNNs
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:736-745
The Cost-free Nature of Optimally Tuning Tikhonov Regularizers and Other Ordered Smoothers
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:746-755
Defense Through Diverse Directions
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:756-766
Interference and Generalization in Temporal Difference Learning
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:767-777
Preselection Bandits
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:778-787
Efficient Policy Learning from Surrogate-Loss Classification Reductions
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:788-798
Training Neural Networks for and by Interpolation
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:799-809
Implicit differentiation of Lasso-type models for hyperparameter optimization
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:810-821
Online Learning with Imperfect Hints
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:822-831
When are Non-Parametric Methods Robust?
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:832-841
Learning and Sampling of Atomic Interventions from Observations
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:842-853
Near-optimal sample complexity bounds for learning Latent $k-$polytopes and applications to Ad-Mixtures
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:854-863
Low-Rank Bottleneck in Multi-head Attention Models
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:864-873
Spectral Clustering with Graph Neural Networks for Graph Pooling
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:874-883
Time Series Deconfounder: Estimating Treatment Effects over Time in the Presence of Hidden Confounders
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:884-895
Adversarial Robustness for Code
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:896-907
The Boomerang Sampler
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:908-918
Tight Bounds on Minimax Regret under Logarithmic Loss via Self-Concordance
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:919-929
My Fair Bandit: Distributed Learning of Max-Min Fairness with Multi-player Bandits
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:930-940
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Provable guarantees for decision tree induction: the agnostic setting
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:941-949
Fast Differentiable Sorting and Ranking
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:950-959
Beyond Signal Propagation: Is Feature Diversity Necessary in Deep Neural Network Initialization?
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:960-969
Modulating Surrogates for Bayesian Optimization
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:970-979
Deep Coordination Graphs
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:980-991
Lorentz Group Equivariant Neural Network for Particle Physics
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:992-1002
Efficient Robustness Certificates for Discrete Data: Sparsity-Aware Randomized Smoothing for Graphs, Images and More
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:1003-1013
Proper Network Interpretability Helps Adversarial Robustness in Classification
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:1014-1023
Spectrum Dependent Learning Curves in Kernel Regression and Wide Neural Networks
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:1024-1034
Small Data, Big Decisions: Model Selection in the Small-Data Regime
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:1035-1044
Latent Variable Modelling with Hyperbolic Normalizing Flows
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:1045-1055
Tightening Exploration in Upper Confidence Reinforcement Learning
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:1056-1066
Preference Modeling with Context-Dependent Salient Features
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:1067-1077
Adversarial Filters of Dataset Biases
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:1078-1088
Calibration, Entropy Rates, and Memory in Language Models
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:1089-1099
Schatten Norms in Matrix Streams: Hello Sparsity, Goodbye Dimension
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:1100-1110
All in the Exponential Family: Bregman Duality in Thermodynamic Variational Inference
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:1111-1122
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Estimating the Number and Effect Sizes of Non-null Hypotheses
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:1123-1133
The FAST Algorithm for Submodular Maximization
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:1134-1143
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GNN-FiLM: Graph Neural Networks with Feature-wise Linear Modulation
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:1144-1152
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TaskNorm: Rethinking Batch Normalization for Meta-Learning
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:1153-1164
Safe Imitation Learning via Fast Bayesian Reward Inference from Preferences
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:1165-1177
A Pairwise Fair and Community-preserving Approach to k-Center Clustering
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:1178-1189
Scalable Exact Inference in Multi-Output Gaussian Processes
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:1190-1201
Online Pricing with Offline Data: Phase Transition and Inverse Square Law
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:1202-1210
[abs][Download PDF]
Empirical Study of the Benefits of Overparameterization in Learning Latent Variable Models
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:1211-1219
DeBayes: a Bayesian Method for Debiasing Network Embeddings
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:1220-1229
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Structured Prediction with Partial Labelling through the Infimum Loss
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:1230-1239
Online Learned Continual Compression with Adaptive Quantization Modules
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:1240-1250
Boosted Histogram Transform for Regression
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:1251-1261
On Validation and Planning of An Optimal Decision Rule with Application in Healthcare Studies
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:1262-1270
Uncertainty quantification for nonconvex tensor completion: Confidence intervals, heteroscedasticity and optimality
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:1271-1282
[abs][Download PDF]
Provably Efficient Exploration in Policy Optimization
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:1283-1294
Near-linear time Gaussian process optimization with adaptive batching and resparsification
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:1295-1305
Poisson Learning: Graph Based Semi-Supervised Learning At Very Low Label Rates
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:1306-1316
Explore, Discover and Learn: Unsupervised Discovery of State-Covering Skills
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:1317-1327
Logarithmic Regret for Learning Linear Quadratic Regulators Efficiently
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:1328-1337
Fully Parallel Hyperparameter Search: Reshaped Space-Filling
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:1338-1348
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Data preprocessing to mitigate bias: A maximum entropy based approach
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:1349-1359
Meta-learning with Stochastic Linear Bandits
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:1360-1370
Description Based Text Classification with Reinforcement Learning
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:1371-1382
Concise Explanations of Neural Networks using Adversarial Training
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:1383-1391
Unlabelled Data Improves Bayesian Uncertainty Calibration under Covariate Shift
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:1392-1402
Imputer: Sequence Modelling via Imputation and Dynamic Programming
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:1403-1413
[abs][Download PDF]
Optimizing for the Future in Non-Stationary MDPs
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:1414-1425
Learning to Simulate and Design for Structural Engineering
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:1426-1436
Decentralized Reinforcement Learning: Global Decision-Making via Local Economic Transactions
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:1437-1447
Invariant Rationalization
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:1448-1458
Circuit-Based Intrinsic Methods to Detect Overfitting
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:1459-1468
[abs][Download PDF]
Better depth-width trade-offs for neural networks through the lens of dynamical systems
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:1469-1478
Explainable and Discourse Topic-aware Neural Language Understanding
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:1479-1488
Uncertainty-Aware Lookahead Factor Models for Quantitative Investing
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:1489-1499
Deep Reasoning Networks for Unsupervised Pattern De-mixing with Constraint Reasoning
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:1500-1509
[abs][Download PDF]
Self-PU: Self Boosted and Calibrated Positive-Unlabeled Training
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:1510-1519
Learning To Stop While Learning To Predict
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:1520-1530
Combinatorial Pure Exploration for Dueling Bandit
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:1531-1541
Graph Optimal Transport for Cross-Domain Alignment
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:1542-1553
[abs][Download PDF][Software]
Stabilizing Differentiable Architecture Search via Perturbation-based Regularization
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:1554-1565
Mapping natural-language problems to formal-language solutions using structured neural representations
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:1566-1575
Convolutional Kernel Networks for Graph-Structured Data
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:1576-1586
Learning Flat Latent Manifolds with VAEs
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:1587-1596
A Simple Framework for Contrastive Learning of Visual Representations
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:1597-1607
Retro*: Learning Retrosynthetic Planning with Neural Guided A* Search
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:1608-1616
Differentiable Product Quantization for End-to-End Embedding Compression
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:1617-1626
On Efficient Constructions of Checkpoints
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:1627-1636
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Angular Visual Hardness
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:1637-1648
Estimating the Error of Randomized Newton Methods: A Bootstrap Approach
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:1649-1659
[abs][Download PDF]
VFlow: More Expressive Generative Flows with Variational Data Augmentation
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:1660-1669
More Data Can Expand The Generalization Gap Between Adversarially Robust and Standard Models
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:1670-1680
An Accelerated DFO Algorithm for Finite-sum Convex Functions
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:1681-1690
Generative Pretraining From Pixels
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:1691-1703
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Negative Sampling in Semi-Supervised learning
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:1704-1714
Optimization from Structured Samples for Coverage Functions
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:1715-1724
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Simple and Deep Graph Convolutional Networks
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:1725-1735
On Breaking Deep Generative Model-based Defenses and Beyond
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:1736-1745
Automated Synthetic-to-Real Generalization
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:1746-1756
[abs][Download PDF][Software]
(Locally) Differentially Private Combinatorial Semi-Bandits
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:1757-1767
High-dimensional Robust Mean Estimation via Gradient Descent
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:1768-1778
CLUB: A Contrastive Log-ratio Upper Bound of Mutual Information
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:1779-1788
Learning with Bounded Instance and Label-dependent Label Noise
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:1789-1799
Mutual Transfer Learning for Massive Data
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:1800-1809
Stochastic Gradient and Langevin Processes
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:1810-1819
Representation Learning via Adversarially-Contrastive Optimal Transport
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:1820-1830
Convergence Rates of Variational Inference in Sparse Deep Learning
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:1831-1842
Reinforcement Learning for Non-Stationary Markov Decision Processes: The Blessing of (More) Optimism
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:1843-1854
[abs][Download PDF]
Streaming Coresets for Symmetric Tensor Factorization
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:1855-1865
On Coresets for Regularized Regression
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:1866-1876
How to Solve Fair k-Center in Massive Data Models
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:1877-1886
Fair Generative Modeling via Weak Supervision
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:1887-1898
Encoding Musical Style with Transformer Autoencoders
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:1899-1908
k-means++: few more steps yield constant approximation
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:1909-1917
Stochastic Flows and Geometric Optimization on the Orthogonal Group
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:1918-1928
Unbiased Risk Estimators Can Mislead: A Case Study of Learning with Complementary Labels
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:1929-1938
Data-Dependent Differentially Private Parameter Learning for Directed Graphical Models
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:1939-1951
Online Continual Learning from Imbalanced Data
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:1952-1961
Distance Metric Learning with Joint Representation Diversification
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:1962-1973
Semismooth Newton Algorithm for Efficient Projections onto $\ell_1, ∞$-norm Ball
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:1974-1983
Estimating Generalization under Distribution Shifts via Domain-Invariant Representations
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:1984-1994
Scalable and Efficient Comparison-based Search without Features
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:1995-2005
Feature-map-level Online Adversarial Knowledge Distillation
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:2006-2015
Teaching with Limited Information on the Learner’s Behaviour
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:2016-2026
Deep Divergence Learning
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:2027-2037
Model Fusion with Kullback-Leibler Divergence
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:2038-2047
Leveraging Procedural Generation to Benchmark Reinforcement Learning
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:2048-2056
Composable Sketches for Functions of Frequencies: Beyond the Worst Case
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:2057-2067
Healing Products of Gaussian Process Experts
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:2068-2077
On Efficient Low Distortion Ultrametric Embedding
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:2078-2088
[abs][Download PDF]
Sub-linear Memory Sketches for Near Neighbor Search on Streaming Data
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:2089-2099
Word-Level Speech Recognition With a Letter to Word Encoder
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:2100-2110
[abs][Download PDF][Software]
Boosting Frank-Wolfe by Chasing Gradients
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:2111-2121
Learning Opinions in Social Networks
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:2122-2132
Relaxing Bijectivity Constraints with Continuously Indexed Normalising Flows
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:2133-2143
Adaptive Region-Based Active Learning
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:2144-2153
Online Learning with Dependent Stochastic Feedback Graphs
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:2154-2163
Learnable Group Transform For Time-Series
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:2164-2173
DINO: Distributed Newton-Type Optimization Method
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:2174-2184
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Causal Modeling for Fairness In Dynamical Systems
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:2185-2195
Minimally distorted Adversarial Examples with a Fast Adaptive Boundary Attack
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:2196-2205
Reliable evaluation of adversarial robustness with an ensemble of diverse parameter-free attacks
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:2206-2216
Real-Time Optimisation for Online Learning in Auctions
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:2217-2226
Privately detecting changes in unknown distributions
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:2227-2237
Flexible and Efficient Long-Range Planning Through Curious Exploration
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:2238-2249
Parameter-free, Dynamic, and Strongly-Adaptive Online Learning
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:2250-2259
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Momentum Improves Normalized SGD
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:2260-2268
Supervised Quantile Normalization for Low Rank Matrix Factorization
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:2269-2279
Double Trouble in Double Descent: Bias and Variance(s) in the Lazy Regime
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:2280-2290
R2-B2: Recursive Reasoning-Based Bayesian Optimization for No-Regret Learning in Games
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:2291-2301
Scalable Deep Generative Modeling for Sparse Graphs
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:2302-2312
The Usual Suspects? Reassessing Blame for VAE Posterior Collapse
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:2313-2322
Confidence Sets and Hypothesis Testing in a Likelihood-Free Inference Setting
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:2323-2334
Goodness-of-Fit Tests for Inhomogeneous Random Graphs
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:2335-2344
Sharp Statistical Guaratees for Adversarially Robust Gaussian Classification
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:2345-2355
Adversarial Attacks on Probabilistic Autoregressive Forecasting Models
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:2356-2365
Subspace Fitting Meets Regression: The Effects of Supervision and Orthonormality Constraints on Double Descent of Generalization Errors
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:2366-2375
Probing Emergent Semantics in Predictive Agents via Question Answering
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:2376-2391
Low-Variance and Zero-Variance Baselines for Extensive-Form Games
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:2392-2401
Combining Differentiable PDE Solvers and Graph Neural Networks for Fluid Flow Prediction
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:2402-2411
Representing Unordered Data Using Complex-Weighted Multiset Automata
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:2412-2420
An end-to-end Differentially Private Latent Dirichlet Allocation Using a Spectral Algorithm
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:2421-2431
Gamification of Pure Exploration for Linear Bandits
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:2432-2442
Structure Adaptive Algorithms for Stochastic Bandits
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:2443-2452
Randomly Projected Additive Gaussian Processes for Regression
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:2453-2463
Interpreting Robust Optimization via Adversarial Influence Functions
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:2464-2473
Non-convex Learning via Replica Exchange Stochastic Gradient MCMC
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:2474-2483
Towards Understanding the Dynamics of the First-Order Adversaries
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:2484-2493
Robust Pricing in Dynamic Mechanism Design
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:2494-2503
A Swiss Army Knife for Minimax Optimal Transport
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:2504-2513
Margin-aware Adversarial Domain Adaptation with Optimal Transport
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:2514-2524
Enhancing Simple Models by Exploiting What They Already Know
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:2525-2534
Spectral Frank-Wolfe Algorithm: Strict Complementarity and Linear Convergence
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:2535-2544
Generalization Guarantees for Sparse Kernel Approximation with Entropic Optimal Features
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:2545-2555
Layered Sampling for Robust Optimization Problems
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:2556-2566
Growing Adaptive Multi-hyperplane Machines
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:2567-2576
Inexact Tensor Methods with Dynamic Accuracies
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:2577-2586
Provable Smoothness Guarantees for Black-Box Variational Inference
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:2587-2596
Optimal Differential Privacy Composition for Exponential Mechanisms
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:2597-2606
Multinomial Logit Bandit with Low Switching Cost
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:2607-2615
Towards Adaptive Residual Network Training: A Neural-ODE Perspective
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:2616-2626
On the Expressivity of Neural Networks for Deep Reinforcement Learning
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:2627-2637
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Collapsed Amortized Variational Inference for Switching Nonlinear Dynamical Systems
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:2638-2647
Expert Learning through Generalized Inverse Multiobjective Optimization: Models, Insights, and Algorithms
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:2648-2657
The Complexity of Finding Stationary Points with Stochastic Gradient Descent
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:2658-2667
Optimal Non-parametric Learning in Repeated Contextual Auctions with Strategic Buyer
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:2668-2677
Reserve Pricing in Repeated Second-Price Auctions with Strategic Bidders
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:2678-2689
NGBoost: Natural Gradient Boosting for Probabilistic Prediction
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:2690-2700
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Minimax-Optimal Off-Policy Evaluation with Linear Function Approximation
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:2701-2709
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Online Bayesian Moment Matching based SAT Solver Heuristics
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:2710-2719
Familywise Error Rate Control by Interactive Unmasking
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:2720-2729
Cooperative Multi-Agent Bandits with Heavy Tails
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:2730-2739
Kernel Methods for Cooperative Multi-Agent Contextual Bandits
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:2740-2750
Optimization Theory for ReLU Neural Networks Trained with Normalization Layers
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:2751-2760
Equivariant Neural Rendering
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:2761-2770
On Contrastive Learning for Likelihood-free Inference
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:2771-2781
Efficient and Scalable Bayesian Neural Nets with Rank-1 Factors
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:2782-2792
Sparse Gaussian Processes with Spherical Harmonic Features
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:2793-2802
Is There a Trade-Off Between Fairness and Accuracy? A Perspective Using Mismatched Hypothesis Testing
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:2803-2813
Self-Concordant Analysis of Frank-Wolfe Algorithms
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:2814-2824
Estimating Q(s,s’) with Deep Deterministic Dynamics Gradients
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:2825-2835
Training Linear Neural Networks: Non-Local Convergence and Complexity Results
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:2836-2847
Student-Teacher Curriculum Learning via Reinforcement Learning: Predicting Hospital Inpatient Admission Location
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:2848-2857
Decision Trees for Decision-Making under the Predict-then-Optimize Framework
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:2858-2867
Revisiting Spatial Invariance with Low-Rank Local Connectivity
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:2868-2879
Divide and Conquer: Leveraging Intermediate Feature Representations for Quantized Training of Neural Networks
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:2880-2891
Generalization Error of Generalized Linear Models in High Dimensions
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:2892-2901
Parallel Algorithm for Non-Monotone DR-Submodular Maximization
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:2902-2911
Continuous Time Bayesian Networks with Clocks
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:2912-2921
Identifying Statistical Bias in Dataset Replication
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:2922-2932
Distributed Online Optimization over a Heterogeneous Network with Any-Batch Mirror Descent
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:2933-2942
Rigging the Lottery: Making All Tickets Winners
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:2943-2952
Faster Graph Embeddings via Coarsening
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:2953-2963
Latent Bernoulli Autoencoder
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:2964-2974
Optimal Sequential Maximization: One Interview is Enough!
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:2975-2984
Spectral Graph Matching and Regularized Quadratic Relaxations: Algorithm and Theory
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:2985-2995
On hyperparameter tuning in general clustering problemsm
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:2996-3007
Online mirror descent and dual averaging: keeping pace in the dynamic case
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:3008-3017
Stochastic Regret Minimization in Extensive-Form Games
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:3018-3028
Do GANs always have Nash equilibria?
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:3029-3039
Growing Action Spaces
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:3040-3051
Improved Optimistic Algorithms for Logistic Bandits
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:3052-3060
Revisiting Fundamentals of Experience Replay
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:3061-3071
Learning with Multiple Complementary Labels
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:3072-3081
Global Concavity and Optimization in a Class of Dynamic Discrete Choice Models
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:3082-3091
The Intrinsic Robustness of Stochastic Bandits to Strategic Manipulation
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:3092-3101
Accountable Off-Policy Evaluation With Kernel Bellman Statistics
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:3102-3111
Kernelized Stein Discrepancy Tests of Goodness-of-fit for Time-to-Event Data
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:3112-3122
Why Are Learned Indexes So Effective?
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:3123-3132
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Implicit Learning Dynamics in Stackelberg Games: Equilibria Characterization, Convergence Analysis, and Empirical Study
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:3133-3144
Can Autonomous Vehicles Identify, Recover From, and Adapt to Distribution Shifts?
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:3145-3153
How to Train Your Neural ODE: the World of Jacobian and Kinetic Regularization
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:3154-3164
Generalizing Convolutional Neural Networks for Equivariance to Lie Groups on Arbitrary Continuous Data
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:3165-3176
Information Particle Filter Tree: An Online Algorithm for POMDPs with Belief-Based Rewards on Continuous Domains
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:3177-3187
Topic Modeling via Full Dependence Mixtures
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:3188-3198
Beyond UCB: Optimal and Efficient Contextual Bandits with Regression Oracles
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:3199-3210
Logarithmic Regret for Adversarial Online Control
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:3211-3221
p-Norm Flow Diffusion for Local Graph Clustering
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:3222-3232
Stochastic Latent Residual Video Prediction
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:3233-3246
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Leveraging Frequency Analysis for Deep Fake Image Recognition
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:3247-3258
Linear Mode Connectivity and the Lottery Ticket Hypothesis
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:3259-3269
No-Regret and Incentive-Compatible Online Learning
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:3270-3279
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Fast and Three-rious: Speeding Up Weak Supervision with Triplet Methods
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:3280-3291
AutoGAN-Distiller: Searching to Compress Generative Adversarial Networks
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:3292-3303
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Don’t Waste Your Bits! Squeeze Activations and Gradients for Deep Neural Networks via TinyScript
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:3304-3314
DessiLBI: Exploring Structural Sparsity of Deep Networks via Differential Inclusion Paths
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:3315-3326
Approximation Guarantees of Local Search Algorithms via Localizability of Set Functions
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:3327-3336
Accelerating the diffusion-based ensemble sampling by non-reversible dynamics
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:3337-3347
Stochastic bandits with arm-dependent delays
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:3348-3356
Abstraction Mechanisms Predict Generalization in Deep Neural Networks
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:3357-3366
A Free-Energy Principle for Representation Learning
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:3367-3376
Can Stochastic Zeroth-Order Frank-Wolfe Method Converge Faster for Non-Convex Problems?
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:3377-3386
Online Convex Optimization in the Random Order Model
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:3387-3396
Symbolic Network: Generalized Neural Policies for Relational MDPs
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:3397-3407
Predicting deliberative outcomes
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:3408-3418
Generalization and Representational Limits of Graph Neural Networks
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:3419-3430
Deep PQR: Solving Inverse Reinforcement Learning using Anchor Actions
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:3431-3441
Multilinear Latent Conditioning for Generating Unseen Attribute Combinations
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:3442-3451
Generalisation error in learning with random features and the hidden manifold model
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:3452-3462
Black-Box Methods for Restoring Monotonicity
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:3463-3473
Online Multi-Kernel Learning with Graph-Structured Feedback
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:3474-3483
Task-Oriented Active Perception and Planning in Environments with Partially Known Semantics
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:3484-3493
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Characterizing Distribution Equivalence and Structure Learning for Cyclic and Acyclic Directed Graphs
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:3494-3504
Private Counting from Anonymous Messages: Near-Optimal Accuracy with Vanishing Communication Overhead
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:3505-3514
Aligned Cross Entropy for Non-Autoregressive Machine Translation
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:3515-3523
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Gradient Temporal-Difference Learning with Regularized Corrections
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:3524-3534
A Distributional Framework For Data Valuation
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:3535-3544
Fractal Gaussian Networks: A sparse random graph model based on Gaussian Multiplicative Chaos
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:3545-3555
Representations for Stable Off-Policy Reinforcement Learning
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:3556-3565
Adaptive Sketching for Fast and Convergent Canonical Polyadic Decomposition
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:3566-3575
One Size Fits All: Can We Train One Denoiser for All Noise Levels?
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:3576-3586
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Superpolynomial Lower Bounds for Learning One-Layer Neural Networks using Gradient Descent
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:3587-3596
SimGANs: Simulator-Based Generative Adversarial Networks for ECG Synthesis to Improve Deep ECG Classification
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:3597-3606
Unraveling Meta-Learning: Understanding Feature Representations for Few-Shot Tasks
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:3607-3616
Towards a General Theory of Infinite-Width Limits of Neural Classifiers
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:3617-3626
Differentially Private Set Union
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:3627-3636
The continuous categorical: a novel simplex-valued exponential family
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:3637-3647
Automatic Reparameterisation of Probabilistic Programs
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:3648-3657
Interpretable Off-Policy Evaluation in Reinforcement Learning by Highlighting Influential Transitions
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:3658-3667
Learning to Navigate The Synthetically Accessible Chemical Space Using Reinforcement Learning
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:3668-3679
Ordinal Non-negative Matrix Factorization for Recommendation
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:3680-3689
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PoWER-BERT: Accelerating BERT Inference via Progressive Word-vector Elimination
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:3690-3699
PackIt: A Virtual Environment for Geometric Planning
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:3700-3710
DROCC: Deep Robust One-Class Classification
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:3711-3721
Scalable Gaussian Process Separation for Kernels with a Non-Stationary Phase
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:3722-3731
Learning the Stein Discrepancy for Training and Evaluating Energy-Based Models without Sampling
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:3732-3747
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On the Iteration Complexity of Hypergradient Computation
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:3748-3758
Robust Learning with the Hilbert-Schmidt Independence Criterion
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:3759-3768
Monte-Carlo Tree Search as Regularized Policy Optimization
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:3769-3778
Near-Tight Margin-Based Generalization Bounds for Support Vector Machines
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:3779-3788
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Implicit Geometric Regularization for Learning Shapes
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:3789-3799
Improving the Gating Mechanism of Recurrent Neural Networks
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:3800-3809
Recurrent Hierarchical Topic-Guided RNN for Language Generation
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:3810-3821
Breaking the Curse of Space Explosion: Towards Efficient NAS with Curriculum Search
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:3822-3831
Certified Data Removal from Machine Learning Models
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:3832-3842
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LTF: A Label Transformation Framework for Correcting Label Shift
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:3843-3853
Learning to Branch for Multi-Task Learning
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:3854-3863
Communication-Efficient Distributed Stochastic AUC Maximization with Deep Neural Networks
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:3864-3874
Bootstrap Latent-Predictive Representations for Multitask Reinforcement Learning
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:3875-3886
Accelerating Large-Scale Inference with Anisotropic Vector Quantization
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:3887-3896
Safe Deep Semi-Supervised Learning for Unseen-Class Unlabeled Data
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:3897-3906
Neural Topic Modeling with Continual Lifelong Learning
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:3907-3917
Multidimensional Shape Constraints
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:3918-3928
Retrieval Augmented Language Model Pre-Training
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:3929-3938
Streaming Submodular Maximization under a k-Set System Constraint
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:3939-3949
Let’s Agree to Agree: Neural Networks Share Classification Order on Real Datasets
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:3950-3960
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Optimal approximation for unconstrained non-submodular minimization
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:3961-3972
FedBoost: A Communication-Efficient Algorithm for Federated Learning
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:3973-3983
Polynomial Tensor Sketch for Element-wise Function of Low-Rank Matrix
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:3984-3993
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DRWR: A Differentiable Renderer without Rendering for Unsupervised 3D Structure Learning from Silhouette Images
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:3994-4005
SIGUA: Forgetting May Make Learning with Noisy Labels More Robust
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:4006-4016
Training Binary Neural Networks through Learning with Noisy Supervision
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:4017-4026
Stochastic Subspace Cubic Newton Method
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:4027-4038
Variance Reduced Coordinate Descent with Acceleration: New Method With a Surprising Application to Finite-Sum Problems
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:4039-4048
Data Amplification: Instance-Optimal Property Estimation
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:4049-4059
Dynamic Knapsack Optimization Towards Efficient Multi-Channel Sequential Advertising
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:4060-4070
Improving generalization by controlling label-noise information in neural network weights
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:4071-4081
A Natural Lottery Ticket Winner: Reinforcement Learning with Ordinary Neural Circuits
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:4082-4093
Bayesian Graph Neural Networks with Adaptive Connection Sampling
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:4094-4104
CoMic: Complementary Task Learning & Mimicry for Reusable Skills
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:4105-4115
Contrastive Multi-View Representation Learning on Graphs
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:4116-4126
Nested Subspace Arrangement for Representation of Relational Data
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:4127-4137
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The Tree Ensemble Layer: Differentiability meets Conditional Computation
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:4138-4148
Compressive sensing with un-trained neural networks: Gradient descent finds a smooth approximation
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:4149-4158
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Hierarchically Decoupled Imitation For Morphological Transfer
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:4159-4171
Gradient-free Online Learning in Continuous Games with Delayed Rewards
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:4172-4181
Data-Efficient Image Recognition with Contrastive Predictive Coding
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:4182-4192
Minimax Rate for Learning From Pairwise Comparisons in the BTL Model
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:4193-4202
Statistically Preconditioned Accelerated Gradient Method for Distributed Optimization
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:4203-4227
Cost-Effective Interactive Attention Learning with Neural Attention Processes
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:4228-4238
Likelihood-free MCMC with Amortized Approximate Ratio Estimators
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:4239-4248
Towards Non-Parametric Drift Detection via Dynamic Adapting Window Independence Drift Detection (DAWIDD)
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:4249-4259
Optimization and Analysis of the pAp@k Metric for Recommender Systems
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:4260-4270
Optimizing Dynamic Structures with Bayesian Generative Search
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:4271-4281
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Learning Task-Agnostic Embedding of Multiple Black-Box Experts for Multi-Task Model Fusion
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:4282-4292
Parameterized Rate-Distortion Stochastic Encoder
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:4293-4303
Topologically Densified Distributions
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:4304-4313
Graph Filtration Learning
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:4314-4323
Black-Box Variational Inference as a Parametric Approximation to Langevin Dynamics
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:4324-4341
Learning Mixtures of Graphs from Epidemic Cascades
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:4342-4352
Set Functions for Time Series
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:4353-4363
Lifted Disjoint Paths with Application in Multiple Object Tracking
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:4364-4375
Infinite attention: NNGP and NTK for deep attention networks
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:4376-4386
The Non-IID Data Quagmire of Decentralized Machine Learning
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:4387-4398
“Other-Play” for Zero-Shot Coordination
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:4399-4410
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XTREME: A Massively Multilingual Multi-task Benchmark for Evaluating Cross-lingual Generalisation
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:4411-4421
Momentum-Based Policy Gradient Methods
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:4422-4433
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From Importance Sampling to Doubly Robust Policy Gradient
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:4434-4443
Evaluating Lossy Compression Rates of Deep Generative Models
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:4444-4454
One Policy to Control Them All: Shared Modular Policies for Agent-Agnostic Control
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:4455-4464
Communication-Efficient Distributed PCA by Riemannian Optimization
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:4465-4474
Improving Transformer Optimization Through Better Initialization
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:4475-4483
More Information Supervised Probabilistic Deep Face Embedding Learning
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:4484-4494
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Generating Programmatic Referring Expressions via Program Synthesis
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:4495-4506
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InstaHide: Instance-hiding Schemes for Private Distributed Learning
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:4507-4518
Accelerated Stochastic Gradient-free and Projection-free Methods
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:4519-4530
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Deep Graph Random Process for Relational-Thinking-Based Speech Recognition
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:4531-4541
Dynamics of Deep Neural Networks and Neural Tangent Hierarchy
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:4542-4551
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Curvature-corrected learning dynamics in deep neural networks
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:4552-4560
Multigrid Neural Memory
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:4561-4571
Meta-Learning with Shared Amortized Variational Inference
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:4572-4582
Linear Lower Bounds and Conditioning of Differentiable Games
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:4583-4593
Fast Deterministic CUR Matrix Decomposition with Accuracy Assurance
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:4594-4603
Do We Need Zero Training Loss After Achieving Zero Training Error?
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:4604-4614
Semi-Supervised Learning with Normalizing Flows
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:4615-4630
Implicit Regularization of Random Feature Models
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:4631-4640
Correlation Clustering with Asymmetric Classification Errors
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:4641-4650
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Optimal Robust Learning of Discrete Distributions from Batches
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:4651-4660
Generalization to New Actions in Reinforcement Learning
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:4661-4672
Tails of Lipschitz Triangular Flows
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:4673-4681
Learning Portable Representations for High-Level Planning
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:4682-4691
Debiased Sinkhorn barycenters
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:4692-4701
Parametric Gaussian Process Regressors
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:4702-4712
Inverse Active Sensing: Modeling and Understanding Timely Decision-Making
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:4713-4723
Source Separation with Deep Generative Priors
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:4724-4735
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Extra-gradient with player sampling for faster convergence in n-player games
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:4736-4745
T-GD: Transferable GAN-generated Images Detection Framework
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:4746-4761
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History-Gradient Aided Batch Size Adaptation for Variance Reduced Algorithms
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:4762-4772
Information-Theoretic Local Minima Characterization and Regularization
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:4773-4783
Optimizing Black-box Metrics with Adaptive Surrogates
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:4784-4793
BINOCULARS for efficient, nonmyopic sequential experimental design
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:4794-4803
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Beyond Synthetic Noise: Deep Learning on Controlled Noisy Labels
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:4804-4815
Implicit Class-Conditioned Domain Alignment for Unsupervised Domain Adaptation
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:4816-4827
Associative Memory in Iterated Overparameterized Sigmoid Autoencoders
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:4828-4838
Hierarchical Generation of Molecular Graphs using Structural Motifs
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:4839-4848
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Multi-Objective Molecule Generation using Interpretable Substructures
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:4849-4859
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Learning Adversarial Markov Decision Processes with Bandit Feedback and Unknown Transition
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:4860-4869
Reward-Free Exploration for Reinforcement Learning
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:4870-4879
What is Local Optimality in Nonconvex-Nonconcave Minimax Optimization?
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:4880-4889
Efficiently Solving MDPs with Stochastic Mirror Descent
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:4890-4900
Computational and Statistical Tradeoffs in Inferring Combinatorial Structures of Ising Model
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:4901-4910
AdaScale SGD: A User-Friendly Algorithm for Distributed Training
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:4911-4920
Guided Learning of Nonconvex Models through Successive Functional Gradient Optimization
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:4921-4930
On Relativistic f-Divergences
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:4931-4939
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Fair k-Centers via Maximum Matching
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:4940-4949
Being Bayesian about Categorical Probability
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:4950-4961
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Evaluating the Performance of Reinforcement Learning Algorithms
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:4962-4973
Stochastic Differential Equations with Variational Wishart Diffusions
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:4974-4983
A simpler approach to accelerated optimization: iterative averaging meets optimism
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:4984-4993
Sets Clustering
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:4994-5005
Distribution Augmentation for Generative Modeling
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:5006-5019
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Sub-Goal Trees a Framework for Goal-Based Reinforcement Learning
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:5020-5030
Partial Trace Regression and Low-Rank Kraus Decomposition
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:5031-5041
Strategyproof Mean Estimation from Multiple-Choice Questions
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:5042-5052
Variational Autoencoders with Riemannian Brownian Motion Priors
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:5053-5066
DeepMatch: Balancing Deep Covariate Representations for Causal Inference Using Adversarial Training
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:5067-5077
Double Reinforcement Learning for Efficient and Robust Off-Policy Evaluation
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:5078-5088
Statistically Efficient Off-Policy Policy Gradients
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:5089-5100
On the Power of Compressed Sensing with Generative Models
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:5101-5109
Learning and Evaluating Contextual Embedding of Source Code
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:5110-5121
Operation-Aware Soft Channel Pruning using Differentiable Masks
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:5122-5131
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SCAFFOLD: Stochastic Controlled Averaging for Federated Learning
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:5132-5143
Non-autoregressive Machine Translation with Disentangled Context Transformer
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:5144-5155
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Transformers are RNNs: Fast Autoregressive Transformers with Linear Attention
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:5156-5165
Rate-distortion optimization guided autoencoder for isometric embedding in Euclidean latent space
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:5166-5176
Efficient Non-conjugate Gaussian Process Factor Models for Spike Count Data using Polynomial Approximations
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:5177-5186
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Quantum Expectation-Maximization for Gaussian mixture models
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:5187-5197
Differentiable Likelihoods for Fast Inversion of ’Likelihood-Free’ Dynamical Systems
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:5198-5208
Feature Noise Induces Loss Discrepancy Across Groups
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:5209-5219
Entropy Minimization In Emergent Languages
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:5220-5230
Private Outsourced Bayesian Optimization
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:5231-5242
What can I do here? A Theory of Affordances in Reinforcement Learning
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:5243-5253
Uniform Convergence of Rank-weighted Learning
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:5254-5263
FACT: A Diagnostic for Group Fairness Trade-offs
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:5264-5274
Puzzle Mix: Exploiting Saliency and Local Statistics for Optimal Mixup
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:5275-5285
Domain Adaptive Imitation Learning
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:5286-5295
Variational Inference for Sequential Data with Future Likelihood Estimates
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:5296-5305
Active World Model Learning with Progress Curiosity
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:5306-5315
Bayesian Experimental Design for Implicit Models by Mutual Information Neural Estimation
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:5316-5326
Optimal Continual Learning has Perfect Memory and is NP-hard
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:5327-5337
Concept Bottleneck Models
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:5338-5348
Learning Similarity Metrics for Numerical Simulations
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:5349-5360
Equivariant Flows: Exact Likelihood Generative Learning for Symmetric Densities
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:5361-5370
Online Learning for Active Cache Synchronization
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:5371-5380
A Unified Theory of Decentralized SGD with Changing Topology and Local Updates
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:5381-5393
Meta-learning for Mixed Linear Regression
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:5394-5404
SDE-Net: Equipping Deep Neural Networks with Uncertainty Estimates
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:5405-5415
On the Sample Complexity of Adversarial Multi-Source PAC Learning
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:5416-5425
Asynchronous Coagent Networks
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:5426-5435
Being Bayesian, Even Just a Bit, Fixes Overconfidence in ReLU Networks
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:5436-5446
A Sequential Self Teaching Approach for Improving Generalization in Sound Event Recognition
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:5447-5457
Curse of Dimensionality on Randomized Smoothing for Certifiable Robustness
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:5458-5467
Understanding Self-Training for Gradual Domain Adaptation
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:5468-5479
On Implicit Regularization in $β$-VAEs
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:5480-5490
Problems with Shapley-value-based explanations as feature importance measures
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:5491-5500
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Efficient Identification in Linear Structural Causal Models with Auxiliary Cutsets
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:5501-5510
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Two Routes to Scalable Credit Assignment without Weight Symmetry
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:5511-5521
Online Dense Subgraph Discovery via Blurred-Graph Feedback
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:5522-5532
Inducing and Exploiting Activation Sparsity for Fast Inference on Deep Neural Networks
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:5533-5543
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Soft Threshold Weight Reparameterization for Learnable Sparsity
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:5544-5555
Controlling Overestimation Bias with Truncated Mixture of Continuous Distributional Quantile Critics
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:5556-5566
Principled learning method for Wasserstein distributionally robust optimization with local perturbations
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:5567-5576
Concentration bounds for CVaR estimation: The cases of light-tailed and heavy-tailed distributions
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:5577-5586
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Optimal Randomized First-Order Methods for Least-Squares Problems
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:5587-5597
Duality in RKHSs with Infinite Dimensional Outputs: Application to Robust Losses
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:5598-5607
Recht-Re Noncommutative Arithmetic-Geometric Mean Conjecture is False
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:5608-5617
Bidirectional Model-based Policy Optimization
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:5618-5627
Robust and Stable Black Box Explanations
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:5628-5638
CURL: Contrastive Unsupervised Representations for Reinforcement Learning
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:5639-5650
Efficient Proximal Mapping of the 1-path-norm of Shallow Networks
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:5651-5661
Learning with Good Feature Representations in Bandits and in RL with a Generative Model
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:5662-5670
Inertial Block Proximal Methods for Non-Convex Non-Smooth Optimization
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:5671-5681
Self-Attentive Associative Memory
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:5682-5691
Causal Effect Identifiability under Partial-Observability
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:5692-5701
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Estimating Model Uncertainty of Neural Networks in Sparse Information Form
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:5702-5713
Self-supervised Label Augmentation via Input Transformations
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:5714-5724
Batch Reinforcement Learning with Hyperparameter Gradients
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:5725-5735
Accelerated Message Passing for Entropy-Regularized MAP Inference
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:5736-5746
Learning Compound Tasks without Task-specific Knowledge via Imitation and Self-supervised Learning
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:5747-5756
Context-aware Dynamics Model for Generalization in Model-Based Reinforcement Learning
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:5757-5766
Temporal Phenotyping using Deep Predictive Clustering of Disease Progression
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:5767-5777
Tensor denoising and completion based on ordinal observations
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:5778-5788
Analytic Marching: An Analytic Meshing Solution from Deep Implicit Surface Networks
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:5789-5798
SGD Learns One-Layer Networks in WGANs
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:5799-5808
Fine-Grained Analysis of Stability and Generalization for Stochastic Gradient Descent
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:5809-5819
Learning Quadratic Games on Networks
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:5820-5830
ACFlow: Flow Models for Arbitrary Conditional Likelihoods
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:5831-5841
Manifold Identification for Ultimately Communication-Efficient Distributed Optimization
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:5842-5852
Neural Architecture Search in A Proxy Validation Loss Landscape
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:5853-5862
PENNI: Pruned Kernel Sharing for Efficient CNN Inference
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:5863-5873
Implicit Euler Skip Connections: Enhancing Adversarial Robustness via Numerical Stability
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:5874-5883
Closed Loop Neural-Symbolic Learning via Integrating Neural Perception, Grammar Parsing, and Symbolic Reasoning
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:5884-5894
Acceleration for Compressed Gradient Descent in Distributed and Federated Optimization
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:5895-5904
On the Relation between Quality-Diversity Evaluation and Distribution-Fitting Goal in Text Generation
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:5905-5915
Latent Space Factorisation and Manipulation via Matrix Subspace Projection
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:5916-5926
Visual Grounding of Learned Physical Models
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:5927-5936
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Learning from Irregularly-Sampled Time Series: A Missing Data Perspective
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:5937-5946
Evolutionary Topology Search for Tensor Network Decomposition
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:5947-5957
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Train Big, Then Compress: Rethinking Model Size for Efficient Training and Inference of Transformers
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:5958-5968
Almost Tune-Free Variance Reduction
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:5969-5978
Nearly Linear Row Sampling Algorithm for Quantile Regression
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:5979-5989
Temporal Logic Point Processes
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:5990-6000
Input-Sparsity Low Rank Approximation in Schatten Norm
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:6001-6009
RIFLE: Backpropagation in Depth for Deep Transfer Learning through Re-Initializing the Fully-connected LayEr
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:6010-6019
On a projective ensemble approach to two sample test for equality of distributions
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:6020-6027
Do We Really Need to Access the Source Data? Source Hypothesis Transfer for Unsupervised Domain Adaptation
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:6028-6039
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Variable Skipping for Autoregressive Range Density Estimation
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:6040-6049
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Adaptive Droplet Routing in Digital Microfluidic Biochips Using Deep Reinforcement Learning
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:6050-6060
AR-DAE: Towards Unbiased Neural Entropy Gradient Estimation
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:6061-6071
Hierarchical Verification for Adversarial Robustness
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:6072-6082
On Gradient Descent Ascent for Nonconvex-Concave Minimax Problems
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:6083-6093
Extrapolation for Large-batch Training in Deep Learning
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:6094-6104
On the Theoretical Properties of the Network Jackknife
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:6105-6115
Handling the Positive-Definite Constraint in the Bayesian Learning Rule
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:6116-6126
InfoGAN-CR and ModelCentrality: Self-supervised Model Training and Selection for Disentangling GANs
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:6127-6139
Improving Generative Imagination in Object-Centric World Models
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:6140-6149
Generalized and Scalable Optimal Sparse Decision Trees
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:6150-6160
Finite-Time Last-Iterate Convergence for Multi-Agent Learning in Games
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:6161-6171
Time-aware Large Kernel Convolutions
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:6172-6183
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Understanding the Curse of Horizon in Off-Policy Evaluation via Conditional Importance Sampling
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:6184-6193
Sparse Shrunk Additive Models
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:6194-6204
Boosting Deep Neural Network Efficiency with Dual-Module Inference
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:6205-6215
Sample Complexity Bounds for 1-bit Compressive Sensing and Binary Stable Embeddings with Generative Priors
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:6216-6225
Peer Loss Functions: Learning from Noisy Labels without Knowing Noise Rates
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:6226-6236
An Imitation Learning Approach for Cache Replacement
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:6237-6247
Exploration Through Reward Biasing: Reward-Biased Maximum Likelihood Estimation for Stochastic Multi-Armed Bandits
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:6248-6258
Hallucinative Topological Memory for Zero-Shot Visual Planning
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:6259-6270
A Chance-Constrained Generative Framework for Sequence Optimization
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:6271-6281
Min-Max Optimization without Gradients: Convergence and Applications to Black-Box Evasion and Poisoning Attacks
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:6282-6293
Median Matrix Completion: from Embarrassment to Optimality
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:6294-6304
A Generic First-Order Algorithmic Framework for Bi-Level Programming Beyond Lower-Level Singleton
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:6305-6315
Learning Deep Kernels for Non-Parametric Two-Sample Tests
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:6316-6326
Learning to Encode Position for Transformer with Continuous Dynamical Model
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:6327-6335
Finding trainable sparse networks through Neural Tangent Transfer
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:6336-6347
Weakly-Supervised Disentanglement Without Compromises
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:6348-6359
Too Relaxed to Be Fair
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:6360-6369
Stochastic Hamiltonian Gradient Methods for Smooth Games
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:6370-6381
Error Estimation for Sketched SVD via the Bootstrap
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:6382-6392
Differentiating through the Fréchet Mean
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:6393-6403
Working Memory Graphs
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:6404-6414
Moniqua: Modulo Quantized Communication in Decentralized SGD
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:6415-6425
A Mean Field Analysis Of Deep ResNet And Beyond: Towards Provably Optimization Via Overparameterization From Depth
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:6426-6436
Countering Language Drift with Seeded Iterated Learning
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:6437-6447
Does label smoothing mitigate label noise?
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:6448-6458
Improved Communication Cost in Distributed PageRank Computation – A Theoretical Study
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:6459-6467
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Progressive Graph Learning for Open-Set Domain Adaptation
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:6468-6478
Adversarial Nonnegative Matrix Factorization
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:6479-6488
Learning Algebraic Multigrid Using Graph Neural Networks
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:6489-6499
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Progressive Identification of True Labels for Partial-Label Learning
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:6500-6510
Bandits with Adversarial Scaling
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:6511-6521
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Efficient Continuous Pareto Exploration in Multi-Task Learning
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:6522-6531
Convex Representation Learning for Generalized Invariance in Semi-Inner-Product Space
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:6532-6542
Normalized Loss Functions for Deep Learning with Noisy Labels
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:6543-6553
Quadratically Regularized Subgradient Methods for Weakly Convex Optimization with Weakly Convex Constraints
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:6554-6564
Understanding the Impact of Model Incoherence on Convergence of Incremental SGD with Random Reshuffle
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:6565-6574
Adversarial Neural Pruning with Latent Vulnerability Suppression
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:6575-6585
Individual Fairness for k-Clustering
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:6586-6596
Multi-Task Learning with User Preferences: Gradient Descent with Controlled Ascent in Pareto Optimization
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:6597-6607
How recurrent networks implement contextual processing in sentiment analysis
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:6608-6619
Anderson Acceleration of Proximal Gradient Methods
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:6620-6629
Convergence of a Stochastic Gradient Method with Momentum for Non-Smooth Non-Convex Optimization
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:6630-6639
Adversarial Robustness Against the Union of Multiple Perturbation Models
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:6640-6650
Evolutionary Reinforcement Learning for Sample-Efficient Multiagent Coordination
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:6651-6660
Estimation of Bounds on Potential Outcomes For Decision Making
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:6661-6671
Optimal transport mapping via input convex neural networks
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:6672-6681
Proving the Lottery Ticket Hypothesis: Pruning is All You Need
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:6682-6691
From Local SGD to Local Fixed-Point Methods for Federated Learning
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:6692-6701
Adaptive Gradient Descent without Descent
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:6702-6712
Emergence of Separable Manifolds in Deep Language Representations
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:6713-6723
Adaptive Adversarial Multi-task Representation Learning
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:6724-6733
On Learning Sets of Symmetric Elements
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:6734-6744
Stochastically Dominant Distributional Reinforcement Learning
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:6745-6754
Minimax Pareto Fairness: A Multi Objective Perspective
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:6755-6764
Predictive Multiplicity in Classification
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:6765-6774
Adding seemingly uninformative labels helps in low data regimes
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:6775-6784
Fast and Consistent Learning of Hidden Markov Models by Incorporating Non-Consecutive Correlations
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:6785-6796
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On Approximate Thompson Sampling with Langevin Algorithms
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:6797-6807
Neural Datalog Through Time: Informed Temporal Modeling via Logical Specification
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:6808-6819
On the Global Convergence Rates of Softmax Policy Gradient Methods
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:6820-6829
Scalable Identification of Partially Observed Systems with Certainty-Equivalent EM
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:6830-6840
Randomized Block-Diagonal Preconditioning for Parallel Learning
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:6841-6851
Training Binary Neural Networks using the Bayesian Learning Rule
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:6852-6861
Control Frequency Adaptation via Action Persistence in Batch Reinforcement Learning
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:6862-6873
The Role of Regularization in Classification of High-dimensional Noisy Gaussian Mixture
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:6874-6883
Projective Preferential Bayesian Optimization
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:6884-6892
VideoOneNet: Bidirectional Convolutional Recurrent OneNet with Trainable Data Steps for Video Processing
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:6893-6904
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The Effect of Natural Distribution Shift on Question Answering Models
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:6905-6916
Strategic Classification is Causal Modeling in Disguise
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:6917-6926
Automatic Shortcut Removal for Self-Supervised Representation Learning
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:6927-6937
Learning Reasoning Strategies in End-to-End Differentiable Proving
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:6938-6949
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Coresets for Data-efficient Training of Machine Learning Models
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:6950-6960
Kinematic State Abstraction and Provably Efficient Rich-Observation Reinforcement Learning
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:6961-6971
Learning to Combine Top-Down and Bottom-Up Signals in Recurrent Neural Networks with Attention over Modules
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:6972-6986
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Optimizing Long-term Social Welfare in Recommender Systems: A Constrained Matching Approach
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:6987-6998
Transformation of ReLU-based recurrent neural networks from discrete-time to continuous-time
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:6999-7009
Efficiently Learning Adversarially Robust Halfspaces with Noise
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:7010-7021
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An end-to-end approach for the verification problem: learning the right distance
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:7022-7033
Confidence-Aware Learning for Deep Neural Networks
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:7034-7044
Topological Autoencoders
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:7045-7054
Explainable k-Means and k-Medians Clustering
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:7055-7065
Fair Learning with Private Demographic Data
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:7066-7075
Consistent Estimators for Learning to Defer to an Expert
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:7076-7087
Continuous-time Lower Bounds for Gradient-based Algorithms
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:7088-7096
Two Simple Ways to Learn Individual Fairness Metrics from Data
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:7097-7107
Unique Properties of Flat Minima in Deep Networks
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:7108-7118
Fast computation of Nash Equilibria in Imperfect Information Games
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:7119-7129
Missing Data Imputation using Optimal Transport
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:7130-7140
Semiparametric Nonlinear Bipartite Graph Representation Learning with Provable Guarantees
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:7141-7152
Full Law Identification in Graphical Models of Missing Data: Completeness Results
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:7153-7163
Voice Separation with an Unknown Number of Multiple Speakers
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:7164-7175
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Reliable Fidelity and Diversity Metrics for Generative Models
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:7176-7185
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From Chaos to Order: Symmetry and Conservation Laws in Game Dynamics
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:7186-7196
Up or Down? Adaptive Rounding for Post-Training Quantization
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:7197-7206
Goal-Aware Prediction: Learning to Model What Matters
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:7207-7219
PolyGen: An Autoregressive Generative Model of 3D Meshes
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:7220-7229
Bayesian Sparsification of Deep C-valued Networks
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:7230-7242
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Oracle Efficient Private Non-Convex Optimization
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:7243-7252
Stochastic Frank-Wolfe for Constrained Finite-Sum Minimization
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:7253-7262
In Defense of Uniform Convergence: Generalization via Derandomization with an Application to Interpolating Predictors
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:7263-7272
Involutive MCMC: a Unifying Framework
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:7273-7282
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Aggregation of Multiple Knockoffs
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:7283-7293
LEEP: A New Measure to Evaluate Transferability of Learned Representations
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:7294-7305
Graph Homomorphism Convolution
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:7306-7316
Knowing The What But Not The Where in Bayesian Optimization
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:7317-7326
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Robust Bayesian Classification Using An Optimistic Score Ratio
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:7327-7337
Streaming k-Submodular Maximization under Noise subject to Size Constraint
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:7338-7347
LP-SparseMAP: Differentiable Relaxed Optimization for Sparse Structured Prediction
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:7348-7359
Semi-Supervised StyleGAN for Disentanglement Learning
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:7360-7369
Supervised learning: no loss no cry
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:7370-7380
Consistent Structured Prediction with Max-Min Margin Markov Networks
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:7381-7391
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T-Basis: a Compact Representation for Neural Networks
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:7392-7404
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Eliminating the Invariance on the Loss Landscape of Linear Autoencoders
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:7405-7413
On the (In)tractability of Computing Normalizing Constants for the Product of Determinantal Point Processes
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:7414-7423
Can Increasing Input Dimensionality Improve Deep Reinforcement Learning?
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:7424-7433
Interferometric Graph Transform: a Deep Unsupervised Graph Representation
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:7434-7444
Learning to Score Behaviors for Guided Policy Optimization
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:7445-7454
Neural Clustering Processes
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:7455-7465
Recovery of Sparse Signals from a Mixture of Linear Samples
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:7466-7475
Adversarial Mutual Information for Text Generation
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:7476-7486
Stabilizing Transformers for Reinforcement Learning
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:7487-7498
Multiresolution Tensor Learning for Efficient and Interpretable Spatial Analysis
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:7499-7509
Meta Variance Transfer: Learning to Augment from the Others
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:7510-7520
Structured Policy Iteration for Linear Quadratic Regulator
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:7521-7531
Regularized Optimal Transport is Ground Cost Adversarial
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:7532-7542
Reducing Sampling Error in Batch Temporal Difference Learning
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:7543-7552
Acceleration through spectral density estimation
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:7553-7562
Einsum Networks: Fast and Scalable Learning of Tractable Probabilistic Circuits
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:7563-7574
Learning Selection Strategies in Buchberger’s Algorithm
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:7575-7585
Non-Autoregressive Neural Text-to-Speech
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:7586-7598
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Performative Prediction
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:7599-7609
Constructive Universal High-Dimensional Distribution Generation through Deep ReLU Networks
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:7610-7619
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Budgeted Online Influence Maximization
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:7620-7631
Low Bias Low Variance Gradient Estimates for Boolean Stochastic Networks
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:7632-7640
On Convergence-Diagnostic based Step Sizes for Stochastic Gradient Descent
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:7641-7651
Sample Factory: Egocentric 3D Control from Pixels at 100000 FPS with Asynchronous Reinforcement Learning
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:7652-7662
IPBoost – Non-Convex Boosting via Integer Programming
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:7663-7672
On Unbalanced Optimal Transport: An Analysis of Sinkhorn Algorithm
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:7673-7682
Scalable Differential Privacy with Certified Robustness in Adversarial Learning
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:7683-7694
Neural Networks are Convex Regularizers: Exact Polynomial-time Convex Optimization Formulations for Two-layer Networks
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:7695-7705
WaveFlow: A Compact Flow-based Model for Raw Audio
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:7706-7716
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Randomization matters How to defend against strong adversarial attacks
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:7717-7727
Efficient Domain Generalization via Common-Specific Low-Rank Decomposition
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:7728-7738
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Dissecting Non-Vacuous Generalization Bounds based on the Mean-Field Approximation
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:7739-7749
Maximum Entropy Gain Exploration for Long Horizon Multi-goal Reinforcement Learning
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:7750-7761
Explaining Groups of Points in Low-Dimensional Representations
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:7762-7771
On the Unreasonable Effectiveness of the Greedy Algorithm: Greedy Adapts to Sharpness
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:7772-7782
Skew-Fit: State-Covering Self-Supervised Reinforcement Learning
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:7783-7792
SoftSort: A Continuous Relaxation for the argsort Operator
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:7793-7802
Graph-based Nearest Neighbor Search: From Practice to Theory
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:7803-7813
Adversarial Risk via Optimal Transport and Optimal Couplings
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:7814-7823
Deep Isometric Learning for Visual Recognition
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:7824-7835
Unsupervised Speech Decomposition via Triple Information Bottleneck
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:7836-7846
Scalable Differentiable Physics for Learning and Control
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:7847-7856
Robust One-Bit Recovery via ReLU Generative Networks: Near-Optimal Statistical Rate and Global Landscape Analysis
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:7857-7866
Few-shot Relation Extraction via Bayesian Meta-learning on Relation Graphs
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:7867-7876
DeepCoDA: personalized interpretability for compositional health data
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:7877-7886
Fast and Private Submodular and $k$-Submodular Functions Maximization with Matroid Constraints
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:7887-7897
Transparency Promotion with Model-Agnostic Linear Competitors
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:7898-7908
Understanding and Mitigating the Tradeoff between Robustness and Accuracy
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:7909-7919
Fast Adaptation to New Environments via Policy-Dynamics Value Functions
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:7920-7931
Improving Robustness of Deep-Learning-Based Image Reconstruction
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:7932-7942
Multi-Precision Policy Enforced Training (MuPPET) : A Precision-Switching Strategy for Quantised Fixed-Point Training of CNNs
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:7943-7952
A Game Theoretic Framework for Model Based Reinforcement Learning
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:7953-7963
Closing the convergence gap of SGD without replacement
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:7964-7973
Policy Teaching via Environment Poisoning: Training-time Adversarial Attacks against Reinforcement Learning
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:7974-7984
Implicit Generative Modeling for Efficient Exploration
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:7985-7995
Universal Equivariant Multilayer Perceptrons
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:7996-8006
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AutoML-Zero: Evolving Machine Learning Algorithms From Scratch
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:8007-8019
Learning Human Objectives by Evaluating Hypothetical Behavior
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:8020-8029
Optimistic Bounds for Multi-output Learning
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:8030-8040
Active Learning on Attributed Graphs via Graph Cognizant Logistic Regression and Preemptive Query Generation
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:8041-8050
The Sample Complexity of Best-$k$ Items Selection from Pairwise Comparisons
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:8051-8072
NetGAN without GAN: From Random Walks to Low-Rank Approximations
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:8073-8082
Normalizing Flows on Tori and Spheres
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:8083-8092
Overfitting in adversarially robust deep learning
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:8093-8104
Decentralised Learning with Random Features and Distributed Gradient Descent
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:8105-8115
Interpretations are Useful: Penalizing Explanations to Align Neural Networks with Prior Knowledge
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:8116-8126
Strength from Weakness: Fast Learning Using Weak Supervision
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:8127-8136
On Semi-parametric Inference for BART
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:8137-8146
FR-Train: A Mutual Information-Based Approach to Fair and Robust Training
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:8147-8157
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Balancing Competing Objectives with Noisy Data: Score-Based Classifiers for Welfare-Aware Machine Learning
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:8158-8168
Double-Loop Unadjusted Langevin Algorithm
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:8169-8177
Reverse-engineering deep ReLU networks
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:8178-8187
Attentive Group Equivariant Convolutional Networks
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:8188-8199
Finite-Time Convergence in Continuous-Time Optimization
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:8200-8209
Near-optimal Regret Bounds for Stochastic Shortest Path
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:8210-8219
Predicting Choice with Set-Dependent Aggregation
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:8220-8229
Certified Robustness to Label-Flipping Attacks via Randomized Smoothing
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:8230-8241
Revisiting Training Strategies and Generalization Performance in Deep Metric Learning
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:8242-8252
FetchSGD: Communication-Efficient Federated Learning with Sketching
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:8253-8265
Simple and sharp analysis of k-means||
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:8266-8275
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Bayesian Optimisation over Multiple Continuous and Categorical Inputs
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:8276-8285
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Inter-domain Deep Gaussian Processes
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:8286-8294
Bio-Inspired Hashing for Unsupervised Similarity Search
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:8295-8306
Adversarial Attacks on Copyright Detection Systems
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:8307-8315
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Bounding the fairness and accuracy of classifiers from population statistics
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:8316-8325
Radioactive data: tracing through training
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:8326-8335
Causal Structure Discovery from Distributions Arising from Mixtures of DAGs
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:8336-8345
An Investigation of Why Overparameterization Exacerbates Spurious Correlations
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:8346-8356
Improved Sleeping Bandits with Stochastic Action Sets and Adversarial Rewards
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:8357-8366
From PAC to Instance-Optimal Sample Complexity in the Plackett-Luce Model
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:8367-8376
Measuring Non-Expert Comprehension of Machine Learning Fairness Metrics
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:8377-8387
From Sets to Multisets: Provable Variational Inference for Probabilistic Integer Submodular Models
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:8388-8397
Counterfactual Cross-Validation: Stable Model Selection Procedure for Causal Inference Models
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:8398-8407
Inferring DQN structure for high-dimensional continuous control
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:8408-8416
The Performance Analysis of Generalized Margin Maximizers on Separable Data
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:8417-8426
Stochastic Coordinate Minimization with Progressive Precision for Stochastic Convex Optimization
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:8427-8437
A Quantile-based Approach for Hyperparameter Transfer Learning
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:8438-8448
Spectral Subsampling MCMC for Stationary Time Series
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:8449-8458
Learning to Simulate Complex Physics with Graph Networks
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:8459-8468
The Impact of Neural Network Overparameterization on Gradient Confusion and Stochastic Gradient Descent
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:8469-8479
Explicit Gradient Learning for Black-Box Optimization
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:8480-8490
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Detecting Out-of-Distribution Examples with Gram Matrices
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:8491-8501
Constrained Markov Decision Processes via Backward Value Functions
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:8502-8511
A Sample Complexity Separation between Non-Convex and Convex Meta-Learning
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:8512-8521
Harmonic Decompositions of Convolutional Networks
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:8522-8532
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Implicit competitive regularization in GANs
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:8533-8544
Off-Policy Actor-Critic with Shared Experience Replay
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:8545-8554
Discriminative Adversarial Search for Abstractive Summarization
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:8555-8564
Universal Average-Case Optimality of Polyak Momentum
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:8565-8572
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Random Matrix Theory Proves that Deep Learning Representations of GAN-data Behave as Gaussian Mixtures
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:8573-8582
Planning to Explore via Self-Supervised World Models
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:8583-8592
An Explicitly Relational Neural Network Architecture
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:8593-8603
Optimistic Policy Optimization with Bandit Feedback
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:8604-8613
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Neural Kernels Without Tangents
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:8614-8623
Learning Robot Skills with Temporal Variational Inference
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:8624-8633
Evaluating Machine Accuracy on ImageNet
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:8634-8644
Channel Equilibrium Networks for Learning Deep Representation
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:8645-8654
ControlVAE: Controllable Variational Autoencoder
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:8655-8664
Lookahead-Bounded Q-learning
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:8665-8675
Causal Strategic Linear Regression
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:8676-8686
Adaptive Sampling for Estimating Probability Distributions
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:8687-8696
PDO-eConvs: Partial Differential Operator Based Equivariant Convolutions
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:8697-8706
Deep Reinforcement Learning with Robust and Smooth Policy
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:8707-8718
Educating Text Autoencoders: Latent Representation Guidance via Denoising
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:8719-8729
Learning for Dose Allocation in Adaptive Clinical Trials with Safety Constraints
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:8730-8740
PowerNorm: Rethinking Batch Normalization in Transformers
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:8741-8751
Extreme Multi-label Classification from Aggregated Labels
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:8752-8762
One-shot Distributed Ridge Regression in High Dimensions
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:8763-8772
Landscape Connectivity and Dropout Stability of SGD Solutions for Over-parameterized Neural Networks
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:8773-8784
Incremental Sampling Without Replacement for Sequence Models
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:8785-8795
Message Passing Least Squares Framework and its Application to Rotation Synchronization
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:8796-8806
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Does the Markov Decision Process Fit the Data: Testing for the Markov Property in Sequential Decision Making
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:8807-8817
A Graph to Graphs Framework for Retrosynthesis Prediction
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:8818-8827
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Informative Dropout for Robust Representation Learning: A Shape-bias Perspective
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:8828-8839
Dispersed Exponential Family Mixture VAEs for Interpretable Text Generation
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:8840-8851
On Conditional Versus Marginal Bias in Multi-Armed Bandits
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:8852-8861
Predictive Coding for Locally-Linear Control
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:8862-8871
A Markov Decision Process Model for Socio-Economic Systems Impacted by Climate Change
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:8872-8883
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Distributionally Robust Policy Evaluation and Learning in Offline Contextual Bandits
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:8884-8894
Piecewise Linear Regression via a Difference of Convex Functions
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:8895-8904
Learning Fair Policies in Multi-Objective (Deep) Reinforcement Learning with Average and Discounted Rewards
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:8905-8915
Deep Gaussian Markov Random Fields
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:8916-8926
Collaborative Machine Learning with Incentive-Aware Model Rewards
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:8927-8936
Naive Exploration is Optimal for Online LQR
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:8937-8948
A Generative Model for Molecular Distance Geometry
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:8949-8958
Reinforcement Learning for Molecular Design Guided by Quantum Mechanics
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:8959-8969
Fractional Underdamped Langevin Dynamics: Retargeting SGD with Momentum under Heavy-Tailed Gradient Noise
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:8970-8980
Second-Order Provable Defenses against Adversarial Attacks
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:8981-8991
FormulaZero: Distributionally Robust Online Adaptation via Offline Population Synthesis
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:8992-9004
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Small-GAN: Speeding up GAN Training using Core-Sets
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:9005-9015
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Interpretable, Multidimensional, Multimodal Anomaly Detection with Negative Sampling for Detection of Device Failure
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:9016-9025
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Structured Linear Contextual Bandits: A Sharp and Geometric Smoothed Analysis
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:9026-9035
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Optimizer Benchmarking Needs to Account for Hyperparameter Tuning
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:9036-9045
When Explanations Lie: Why Many Modified BP Attributions Fail
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:9046-9057
On the Generalization Benefit of Noise in Stochastic Gradient Descent
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:9058-9067
Multiclass Neural Network Minimization via Tropical Newton Polytope Approximation
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:9068-9077
Bridging the Gap Between f-GANs and Wasserstein GANs
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:9078-9087
Provably Efficient Model-based Policy Adaptation
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:9088-9098
Hypernetwork approach to generating point clouds
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:9099-9108
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Robustness to Spurious Correlations via Human Annotations
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:9109-9119
Which Tasks Should Be Learned Together in Multi-task Learning?
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:9120-9132
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Responsive Safety in Reinforcement Learning by PID Lagrangian Methods
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:9133-9143
Learning Discrete Structured Representations by Adversarially Maximizing Mutual Information
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:9144-9154
Confidence-Calibrated Adversarial Training: Generalizing to Unseen Attacks
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:9155-9166
Doubly robust off-policy evaluation with shrinkage
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:9167-9176
Task Understanding from Confusing Multi-task Data
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:9177-9186
ConQUR: Mitigating Delusional Bias in Deep Q-Learning
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:9187-9195
Adaptive Estimator Selection for Off-Policy Evaluation
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:9196-9205
Generative Teaching Networks: Accelerating Neural Architecture Search by Learning to Generate Synthetic Training Data
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:9206-9216
Improving the Sample and Communication Complexity for Decentralized Non-Convex Optimization: Joint Gradient Estimation and Tracking
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:9217-9228
Test-Time Training with Self-Supervision for Generalization under Distribution Shifts
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:9229-9248
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An EM Approach to Non-autoregressive Conditional Sequence Generation
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:9249-9258
The Shapley Taylor Interaction Index
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:9259-9268
The Many Shapley Values for Model Explanation
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:9269-9278
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Multi-objective Bayesian Optimization using Pareto-frontier Entropy
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:9279-9288
The k-tied Normal Distribution: A Compact Parameterization of Gaussian Mean Field Posteriors in Bayesian Neural Networks
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:9289-9299
Multi-Agent Routing Value Iteration Network
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:9300-9310
Distinguishing Cause from Effect Using Quantiles: Bivariate Quantile Causal Discovery
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:9311-9323
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Quantized Decentralized Stochastic Learning over Directed Graphs
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:9324-9333
Multi-fidelity Bayesian Optimization with Max-value Entropy Search and its Parallelization
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:9334-9345
Fiedler Regularization: Learning Neural Networks with Graph Sparsity
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:9346-9355
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DropNet: Reducing Neural Network Complexity via Iterative Pruning
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:9356-9366
Reinforcement Learning for Integer Programming: Learning to Cut
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:9367-9376
The Buckley-Osthus model and the block preferential attachment model: statistical analysis and application
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:9377-9386
Clinician-in-the-Loop Decision Making: Reinforcement Learning with Near-Optimal Set-Valued Policies
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:9387-9396
Taylor Expansion Policy Optimization
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:9397-9406
Variational Imitation Learning with Diverse-quality Demonstrations
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:9407-9417
Learning disconnected manifolds: a no GAN’s land
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:9418-9427
No-Regret Exploration in Goal-Oriented Reinforcement Learning
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:9428-9437
Sparse Sinkhorn Attention
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:9438-9447
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Inductive Relation Prediction by Subgraph Reasoning
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:9448-9457
Few-shot Domain Adaptation by Causal Mechanism Transfer
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:9458-9469
Student Specialization in Deep Rectified Networks With Finite Width and Input Dimension
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:9470-9480
Sequential Transfer in Reinforcement Learning with a Generative Model
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:9481-9492
Convolutional dictionary learning based auto-encoders for natural exponential-family distributions
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:9493-9503
Multi-step Greedy Reinforcement Learning Algorithms
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:9504-9513
Choice Set Optimization Under Discrete Choice Models of Group Decisions
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:9514-9525
TrajectoryNet: A Dynamic Optimal Transport Network for Modeling Cellular Dynamics
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:9526-9536
Alleviating Privacy Attacks via Causal Learning
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:9537-9547
Bayesian Learning from Sequential Data using Gaussian Processes with Signature Covariances
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:9548-9560
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Fundamental Tradeoffs between Invariance and Sensitivity to Adversarial Perturbations
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:9561-9571
Stochastic Gauss-Newton Algorithms for Nonconvex Compositional Optimization
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:9572-9582
Bayesian Differential Privacy for Machine Learning
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:9583-9592
Single Point Transductive Prediction
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:9593-9602
GraphOpt: Learning Optimization Models of Graph Formation
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:9603-9613
Transfer Learning without Knowing: Reprogramming Black-box Machine Learning Models with Scarce Data and Limited Resources
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:9614-9624
From ImageNet to Image Classification: Contextualizing Progress on Benchmarks
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:9625-9635
Normalized Flat Minima: Exploring Scale Invariant Definition of Flat Minima for Neural Networks Using PAC-Bayesian Analysis
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:9636-9647
Approximating Stacked and Bidirectional Recurrent Architectures with the Delayed Recurrent Neural Network
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:9648-9658
Minimax Weight and Q-Function Learning for Off-Policy Evaluation
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:9659-9668
StochasticRank: Global Optimization of Scale-Free Discrete Functions
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:9669-9679
Undirected Graphical Models as Approximate Posteriors
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:9680-9689
Uncertainty Estimation Using a Single Deep Deterministic Neural Network
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:9690-9700
Deep Molecular Programming: A Natural Implementation of Binary-Weight ReLU Neural Networks
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:9701-9711
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Linear bandits with Stochastic Delayed Feedback
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:9712-9721
Non-Stationary Delayed Bandits with Intermediate Observations
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:9722-9732
OPtions as REsponses: Grounding behavioural hierarchies in multi-agent reinforcement learning
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:9733-9742
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Born-Again Tree Ensembles
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:9743-9753
Private Reinforcement Learning with PAC and Regret Guarantees
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:9754-9764
New Oracle-Efficient Algorithms for Private Synthetic Data Release
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:9765-9774
Conditional gradient methods for stochastically constrained convex minimization
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:9775-9785
Unsupervised Discovery of Interpretable Directions in the GAN Latent Space
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:9786-9796
Safe Reinforcement Learning in Constrained Markov Decision Processes
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:9797-9806
Orthogonalized SGD and Nested Architectures for Anytime Neural Networks
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:9807-9817
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Projection-free Distributed Online Convex Optimization with $O(\sqrtT)$ Communication Complexity
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:9818-9828
Logistic Regression for Massive Data with Rare Events
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:9829-9836
On the Global Optimality of Model-Agnostic Meta-Learning
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:9837-9846
Towards Accurate Post-training Network Quantization via Bit-Split and Stitching
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:9847-9856
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Self-Modulating Nonparametric Event-Tensor Factorization
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:9857-9867
Upper bounds for Model-Free Row-Sparse Principal Component Analysis
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:9868-9875
ROMA: Multi-Agent Reinforcement Learning with Emergent Roles
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:9876-9886
Non-separable Non-stationary random fields
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:9887-9897
Continuously Indexed Domain Adaptation
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:9898-9907
Learning Efficient Multi-agent Communication: An Information Bottleneck Approach
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:9908-9918
Frustratingly Simple Few-Shot Object Detection
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:9919-9928
Understanding Contrastive Representation Learning through Alignment and Uniformity on the Hypersphere
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:9929-9939
Enhanced POET: Open-ended Reinforcement Learning through Unbounded Invention of Learning Challenges and their Solutions
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:9940-9951
Haar Graph Pooling
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:9952-9962
Deep Streaming Label Learning
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:9963-9972
BoXHED: Boosted eXact Hazard Estimator with Dynamic covariates
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:9973-9982
Optimizing Data Usage via Differentiable Rewards
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:9983-9995
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Bandits for BMO Functions
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:9996-10006
When deep denoising meets iterative phase retrieval
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:10007-10017
Doubly Stochastic Variational Inference for Neural Processes with Hierarchical Latent Variables
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:10018-10028
Loss Function Search for Face Recognition
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:10029-10038
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Sequential Cooperative Bayesian Inference
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:10039-10049
Neural Network Control Policy Verification With Persistent Adversarial Perturbation
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:10050-10059
Cost-effectively Identifying Causal Effects When Only Response Variable is Observable
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:10060-10069
Striving for Simplicity and Performance in Off-Policy DRL: Output Normalization and Non-Uniform Sampling
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:10070-10080
On Differentially Private Stochastic Convex Optimization with Heavy-tailed Data
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:10081-10091
Breaking the Curse of Many Agents: Provable Mean Embedding Q-Iteration for Mean-Field Reinforcement Learning
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:10092-10103
On Lp-norm Robustness of Ensemble Decision Stumps and Trees
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:10104-10114
Thompson Sampling via Local Uncertainty
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:10115-10125
A Nearly-Linear Time Algorithm for Exact Community Recovery in Stochastic Block Model
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:10126-10135
Learning Representations that Support Extrapolation
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:10136-10146
Tuning-free Plug-and-Play Proximal Algorithm for Inverse Imaging Problems
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:10158-10169
Model-free Reinforcement Learning in Infinite-horizon Average-reward Markov Decision Processes
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:10170-10180
The Implicit and Explicit Regularization Effects of Dropout
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:10181-10192
Online Control of the False Coverage Rate and False Sign Rate
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:10193-10202
Batch Stationary Distribution Estimation
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:10203-10213
Domain Aggregation Networks for Multi-Source Domain Adaptation
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:10214-10224
Towards Understanding the Regularization of Adversarial Robustness on Neural Networks
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:10225-10235
Amortised Learning by Wake-Sleep
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:10236-10247
How Good is the Bayes Posterior in Deep Neural Networks Really?
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:10248-10259
Predictive Sampling with Forecasting Autoregressive Models
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:10260-10269
State Space Expectation Propagation: Efficient Inference Schemes for Temporal Gaussian Processes
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:10270-10281
Efficient nonparametric statistical inference on population feature importance using Shapley values
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:10282-10291
Efficiently sampling functions from Gaussian process posteriors
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:10292-10302
Learning to Rank Learning Curves
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:10303-10312
Causal Inference using Gaussian Processes with Structured Latent Confounders
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:10313-10323
Near Input Sparsity Time Kernel Embeddings via Adaptive Sampling
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:10324-10333
Is Local SGD Better than Minibatch SGD?
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:10334-10343
Obtaining Adjustable Regularization for Free via Iterate Averaging
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:10344-10354
DeltaGrad: Rapid retraining of machine learning models
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:10355-10366
On the Noisy Gradient Descent that Generalizes as SGD
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:10367-10376
Stronger and Faster Wasserstein Adversarial Attacks
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:10377-10387
Sequence Generation with Mixed Representations
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:10388-10398
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Adversarial Robustness via Runtime Masking and Cleansing
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:10399-10409
On the Generalization Effects of Linear Transformations in Data Augmentation
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:10410-10420
Amortized Population Gibbs Samplers with Neural Sufficient Statistics
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:10421-10431
Continuous Graph Neural Networks
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:10432-10441
A Flexible Framework for Nonparametric Graphical Modeling that Accommodates Machine Learning
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:10442-10451
Generative Flows with Matrix Exponential
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:10452-10461
Disentangling Trainability and Generalization in Deep Neural Networks
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:10462-10472
Optimally Solving Two-Agent Decentralized POMDPs Under One-Sided Information Sharing
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:10473-10482
Maximum-and-Concatenation Networks
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:10483-10494
Zeno++: Robust Fully Asynchronous SGD
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:10495-10503
Lower Complexity Bounds for Finite-Sum Convex-Concave Minimax Optimization Problems
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:10504-10513
On the Number of Linear Regions of Convolutional Neural Networks
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:10514-10523
On Layer Normalization in the Transformer Architecture
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:10524-10533
On Variational Learning of Controllable Representations for Text without Supervision
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:10534-10543
Class-Weighted Classification: Trade-offs and Robust Approaches
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:10544-10554
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A Finite-Time Analysis of Q-Learning with Neural Network Function Approximation
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:10555-10565
Understanding and Stabilizing GANs’ Training Dynamics Using Control Theory
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:10566-10575
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Learning Autoencoders with Relational Regularization
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:10576-10586
Learning Factorized Weight Matrix for Joint Filtering
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:10587-10596
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Variational Label Enhancement
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:10597-10606
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Prediction-Guided Multi-Objective Reinforcement Learning for Continuous Robot Control
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:10607-10616
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MetaFun: Meta-Learning with Iterative Functional Updates
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:10617-10627
Video Prediction via Example Guidance
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:10628-10637
Amortized Finite Element Analysis for Fast PDE-Constrained Optimization
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:10638-10647
Feature Selection using Stochastic Gates
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:10648-10659
Stochastic Optimization for Non-convex Inf-Projection Problems
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:10660-10669
Variational Bayesian Quantization
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:10670-10680
Energy-Based Processes for Exchangeable Data
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:10681-10692
Randomized Smoothing of All Shapes and Sizes
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:10693-10705
Q-value Path Decomposition for Deep Multiagent Reinforcement Learning
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:10706-10715
Improving Molecular Design by Stochastic Iterative Target Augmentation
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:10716-10726
On the consistency of top-k surrogate losses
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:10727-10735
Interpolation between Residual and Non-Residual Networks
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:10736-10745
Reinforcement Learning in Feature Space: Matrix Bandit, Kernels, and Regret Bound
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:10746-10756
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Multi-Agent Determinantal Q-Learning
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:10757-10766
Rethinking Bias-Variance Trade-off for Generalization of Neural Networks
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:10767-10777
Unsupervised Transfer Learning for Spatiotemporal Predictive Networks
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:10778-10788
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Searching to Exploit Memorization Effect in Learning with Noisy Labels
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:10789-10798
Graph-based, Self-Supervised Program Repair from Diagnostic Feedback
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:10799-10808
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Pretrained Generalized Autoregressive Model with Adaptive Probabilistic Label Clusters for Extreme Multi-label Text Classification
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:10809-10819
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Good Subnetworks Provably Exist: Pruning via Greedy Forward Selection
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:10820-10830
It’s Not What Machines Can Learn, It’s What We Cannot Teach
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:10831-10841
Data Valuation using Reinforcement Learning
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:10842-10851
XtarNet: Learning to Extract Task-Adaptive Representation for Incremental Few-Shot Learning
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:10852-10860
Robustifying Sequential Neural Processes
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:10861-10870
When Does Self-Supervision Help Graph Convolutional Networks?
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:10871-10880
Graph Structure of Neural Networks
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:10881-10891
Simultaneous Inference for Massive Data: Distributed Bootstrap
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:10892-10901
Graphical Models Meet Bandits: A Variational Thompson Sampling Approach
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:10902-10912
Label-Noise Robust Domain Adaptation
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:10913-10924
Intrinsic Reward Driven Imitation Learning via Generative Model
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:10925-10935
Graph Convolutional Network for Recommendation with Low-pass Collaborative Filters
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:10936-10945
Federated Learning with Only Positive Labels
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:10946-10956
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Training Deep Energy-Based Models with f-Divergence Minimization
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:10957-10967
Graph Random Neural Features for Distance-Preserving Graph Representations
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:10968-10977
Learning Near Optimal Policies with Low Inherent Bellman Error
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:10978-10989
Scaling up Hybrid Probabilistic Inference with Logical and Arithmetic Constraints via Message Passing
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:10990-11000
Learning Calibratable Policies using Programmatic Style-Consistency
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:11001-11011
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Designing Optimal Dynamic Treatment Regimes: A Causal Reinforcement Learning Approach
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:11012-11022
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Robustness to Programmable String Transformations via Augmented Abstract Training
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:11023-11032
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Converging to Team-Maxmin Equilibria in Zero-Sum Multiplayer Games
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:11033-11043
Generative Adversarial Imitation Learning with Neural Network Parameterization: Global Optimality and Convergence Rate
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:11044-11054
Cautious Adaptation For Reinforcement Learning in Safety-Critical Settings
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:11055-11065
Learning the Valuations of a $k$-demand Agent
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:11066-11075
A Tree-Structured Decoder for Image-to-Markup Generation
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:11076-11085
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Approximation Capabilities of Neural ODEs and Invertible Residual Networks
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:11086-11095
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Random Hypervolume Scalarizations for Provable Multi-Objective Black Box Optimization
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:11096-11105
Spread Divergence
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:11106-11116
Mix-n-Match : Ensemble and Compositional Methods for Uncertainty Calibration in Deep Learning
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:11117-11128
Privately Learning Markov Random Fields
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:11129-11140
Learning Structured Latent Factors from Dependent Data:A Generative Model Framework from Information-Theoretic Perspective
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:11141-11152
Optimal Estimator for Unlabeled Linear Regression
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:11153-11162
Dual-Path Distillation: A Unified Framework to Improve Black-Box Attacks
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:11163-11172
Complexity of Finding Stationary Points of Nonconvex Nonsmooth Functions
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:11173-11182
Self-Attentive Hawkes Process
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:11183-11193
GradientDICE: Rethinking Generalized Offline Estimation of Stationary Values
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:11194-11203
Provably Convergent Two-Timescale Off-Policy Actor-Critic with Function Approximation
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:11204-11213
Invariant Causal Prediction for Block MDPs
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:11214-11224
Adaptive Reward-Poisoning Attacks against Reinforcement Learning
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:11225-11234
CAUSE: Learning Granger Causality from Event Sequences using Attribution Methods
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:11235-11245
Convex Calibrated Surrogates for the Multi-Label F-Measure
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:11246-11255
Sparsified Linear Programming for Zero-Sum Equilibrium Finding
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:11256-11267
Fast Learning of Graph Neural Networks with Guaranteed Generalizability: One-hidden-layer Case
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:11268-11277
Attacks Which Do Not Kill Training Make Adversarial Learning Stronger
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:11278-11287
A Flexible Latent Space Model for Multilayer Networks
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:11288-11297
Perceptual Generative Autoencoders
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:11298-11306
Variance Reduction in Stochastic Particle-Optimization Sampling
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:11307-11316
Learning with Feature and Distribution Evolvable Streams
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:11317-11327
PEGASUS: Pre-training with Extracted Gap-sentences for Abstractive Summarization
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:11328-11339
On Leveraging Pretrained GANs for Generation with Limited Data
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:11340-11351
On Learning Language-Invariant Representations for Universal Machine Translation
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:11352-11364
Do RNN and LSTM have Long Memory?
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:11365-11375
Feature Quantization Improves GAN Training
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:11376-11386
Individual Calibration with Randomized Forecasting
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:11387-11397
Smaller, more accurate regression forests using tree alternating optimization
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:11398-11408
Learning to Learn Kernels with Variational Random Features
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:11409-11419
Sharp Composition Bounds for Gaussian Differential Privacy via Edgeworth Expansion
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:11420-11435
What Can Learned Intrinsic Rewards Capture?
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:11436-11446
Error-Bounded Correction of Noisy Labels
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:11447-11457
Robust Graph Representation Learning via Neural Sparsification
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:11458-11468
Bisection-Based Pricing for Repeated Contextual Auctions against Strategic Buyer
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:11469-11480
Best Arm Identification for Cascading Bandits in the Fixed Confidence Setting
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:11481-11491
Neural Contextual Bandits with UCB-based Exploration
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:11492-11502
MoNet3D: Towards Accurate Monocular 3D Object Localization in Real Time
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:11503-11512
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Nonparametric Score Estimators
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:11513-11522
Time-Consistent Self-Supervision for Semi-Supervised Learning
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:11523-11533
Divide, Conquer, and Combine: a New Inference Strategy for Probabilistic Programs with Stochastic Support
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:11534-11545
Go Wide, Then Narrow: Efficient Training of Deep Thin Networks
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:11546-11555
Hybrid Stochastic-Deterministic Minibatch Proximal Gradient: Less-Than-Single-Pass Optimization with Nearly Optimal Generalization
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:11556-11565
Robust Outlier Arm Identification
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:11566-11575
Variance Reduction and Quasi-Newton for Particle-Based Variational Inference
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:11576-11587
Causal Effect Estimation and Optimal Dose Suggestions in Mobile Health
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:11588-11598
Thompson Sampling Algorithms for Mean-Variance Bandits
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:11599-11608
Learning Adversarially Robust Representations via Worst-Case Mutual Information Maximization
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:11609-11618
Linear Convergence of Randomized Primal-Dual Coordinate Method for Large-scale Linear Constrained Convex Programming
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:11619-11628
When Demands Evolve Larger and Noisier: Learning and Earning in a Growing Environment
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:11629-11638
Adaptive Checkpoint Adjoint Method for Gradient Estimation in Neural ODE
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:11639-11649
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Learning Optimal Tree Models under Beam Search
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:11650-11659
Laplacian Regularized Few-Shot Learning
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:11660-11670
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Influenza Forecasting Framework based on Gaussian Processes
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:11671-11679
A general recurrent state space framework for modeling neural dynamics during decision-making
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:11680-11691
Transformer Hawkes Process
; Proceedings of the 37th International Conference on Machine Learning, PMLR 119:11692-11702
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