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Volume 161: Uncertainty in Artificial Intelligence, 27-30 July 2021, Online
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Editors: Cassio de Campos, Marloes H. Maathuis
Proceedings of the thirty-seventh conference on Uncertainty in Artificial Intelligence — Preface
; Proceedings of the Thirty-Seventh Conference on Uncertainty in Artificial Intelligence, PMLR 161:1-11
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The neural moving average model for scalable variational inference of state space models
; Proceedings of the Thirty-Seventh Conference on Uncertainty in Artificial Intelligence, PMLR 161:12-22
Task similarity aware meta learning: theory-inspired improvement on MAML
; Proceedings of the Thirty-Seventh Conference on Uncertainty in Artificial Intelligence, PMLR 161:23-33
Efficient debiased evidence estimation by multilevel Monte Carlo sampling
; Proceedings of the Thirty-Seventh Conference on Uncertainty in Artificial Intelligence, PMLR 161:34-43
Variational inference with continuously-indexed normalizing flows
; Proceedings of the Thirty-Seventh Conference on Uncertainty in Artificial Intelligence, PMLR 161:44-53
TreeBERT: A tree-based pre-trained model for programming language
; Proceedings of the Thirty-Seventh Conference on Uncertainty in Artificial Intelligence, PMLR 161:54-63
Competitive policy optimization
; Proceedings of the Thirty-Seventh Conference on Uncertainty in Artificial Intelligence, PMLR 161:64-74
Improving uncertainty calibration of deep neural networks via truth discovery and geometric optimization
; Proceedings of the Thirty-Seventh Conference on Uncertainty in Artificial Intelligence, PMLR 161:75-85
Incorporating causal graphical prior knowledge into predictive modeling via simple data augmentation
; Proceedings of the Thirty-Seventh Conference on Uncertainty in Artificial Intelligence, PMLR 161:86-96
Causal additive models with unobserved variables
; Proceedings of the Thirty-Seventh Conference on Uncertainty in Artificial Intelligence, PMLR 161:97-106
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A variational approximation for analyzing the dynamics of panel data
; Proceedings of the Thirty-Seventh Conference on Uncertainty in Artificial Intelligence, PMLR 161:107-117
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Graph reparameterizations for enabling 1000+ Monte Carlo iterations in Bayesian deep neural networks
; Proceedings of the Thirty-Seventh Conference on Uncertainty in Artificial Intelligence, PMLR 161:118-128
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The curious case of adversarially robust models: More data can help, double descend, or hurt generalization
; Proceedings of the Thirty-Seventh Conference on Uncertainty in Artificial Intelligence, PMLR 161:129-139
Contrastive prototype learning with augmented embeddings for few-shot learning
; Proceedings of the Thirty-Seventh Conference on Uncertainty in Artificial Intelligence, PMLR 161:140-150
XOR-SGD: provable convex stochastic optimization for decision-making under uncertainty
; Proceedings of the Thirty-Seventh Conference on Uncertainty in Artificial Intelligence, PMLR 161:151-160
Path dependent structural equation models
; Proceedings of the Thirty-Seventh Conference on Uncertainty in Artificial Intelligence, PMLR 161:161-171
Featurized density ratio estimation
; Proceedings of the Thirty-Seventh Conference on Uncertainty in Artificial Intelligence, PMLR 161:172-182
Variance reduction in frequency estimators via control variates method
; Proceedings of the Thirty-Seventh Conference on Uncertainty in Artificial Intelligence, PMLR 161:183-193
Application of kernel hypothesis testing on set-valued data
; Proceedings of the Thirty-Seventh Conference on Uncertainty in Artificial Intelligence, PMLR 161:194-204
A kernel two-sample test with selection bias
; Proceedings of the Thirty-Seventh Conference on Uncertainty in Artificial Intelligence, PMLR 161:205-214
An unsupervised video game playstyle metric via state discretization
; Proceedings of the Thirty-Seventh Conference on Uncertainty in Artificial Intelligence, PMLR 161:215-224
Most: multi-source domain adaptation via optimal transport for student-teacher learning
; Proceedings of the Thirty-Seventh Conference on Uncertainty in Artificial Intelligence, PMLR 161:225-235
Constrained labeling for weakly supervised learning
; Proceedings of the Thirty-Seventh Conference on Uncertainty in Artificial Intelligence, PMLR 161:236-246
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Communication efficient parallel reinforcement learning
; Proceedings of the Thirty-Seventh Conference on Uncertainty in Artificial Intelligence, PMLR 161:247-256
Robust reinforcement learning under minimax regret for green security
; Proceedings of the Thirty-Seventh Conference on Uncertainty in Artificial Intelligence, PMLR 161:257-267
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Defending SVMs against poisoning attacks: the hardness and DBSCAN approach
; Proceedings of the Thirty-Seventh Conference on Uncertainty in Artificial Intelligence, PMLR 161:268-278
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Matrix games with bandit feedback
; Proceedings of the Thirty-Seventh Conference on Uncertainty in Artificial Intelligence, PMLR 161:279-289
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Improving approximate optimal transport distances using quantization
; Proceedings of the Thirty-Seventh Conference on Uncertainty in Artificial Intelligence, PMLR 161:290-300
Approximate implication with d-separation
; Proceedings of the Thirty-Seventh Conference on Uncertainty in Artificial Intelligence, PMLR 161:301-311
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Hierarchical probabilistic model for blind source separation via Legendre transformation
; Proceedings of the Thirty-Seventh Conference on Uncertainty in Artificial Intelligence, PMLR 161:312-321
Lifted reasoning meets weighted model integration
; Proceedings of the Thirty-Seventh Conference on Uncertainty in Artificial Intelligence, PMLR 161:322-332
Formal verification of neural networks for safety-critical tasks in deep reinforcement learning
; Proceedings of the Thirty-Seventh Conference on Uncertainty in Artificial Intelligence, PMLR 161:333-343
Learnable uncertainty under Laplace approximations
; Proceedings of the Thirty-Seventh Conference on Uncertainty in Artificial Intelligence, PMLR 161:344-353
Symmetric Wasserstein autoencoders
; Proceedings of the Thirty-Seventh Conference on Uncertainty in Artificial Intelligence, PMLR 161:354-364
Unsupervised anomaly detection with adversarial mirrored autoencoders
; Proceedings of the Thirty-Seventh Conference on Uncertainty in Artificial Intelligence, PMLR 161:365-375
Action redundancy in reinforcement learning
; Proceedings of the Thirty-Seventh Conference on Uncertainty in Artificial Intelligence, PMLR 161:376-385
Weighted model counting with conditional weights for Bayesian networks
; Proceedings of the Thirty-Seventh Conference on Uncertainty in Artificial Intelligence, PMLR 161:386-396
Escaping from zero gradient: Revisiting action-constrained reinforcement learning via Frank-Wolfe policy optimization
; Proceedings of the Thirty-Seventh Conference on Uncertainty in Artificial Intelligence, PMLR 161:397-407
Unsupervised program synthesis for images by sampling without replacement
; Proceedings of the Thirty-Seventh Conference on Uncertainty in Artificial Intelligence, PMLR 161:408-418
On the distributional properties of adaptive gradients
; Proceedings of the Thirty-Seventh Conference on Uncertainty in Artificial Intelligence, PMLR 161:419-429
Bandits with partially observable confounded data
; Proceedings of the Thirty-Seventh Conference on Uncertainty in Artificial Intelligence, PMLR 161:430-439
Structured sparsification with joint optimization of group convolution and channel shuffle
; Proceedings of the Thirty-Seventh Conference on Uncertainty in Artificial Intelligence, PMLR 161:440-450
A weaker faithfulness assumption based on triple interactions
; Proceedings of the Thirty-Seventh Conference on Uncertainty in Artificial Intelligence, PMLR 161:451-460
pRSL: Interpretable multi-label stacking by learning probabilistic rules
; Proceedings of the Thirty-Seventh Conference on Uncertainty in Artificial Intelligence, PMLR 161:461-470
Regstar: efficient strategy synthesis for adversarial patrolling games
; Proceedings of the Thirty-Seventh Conference on Uncertainty in Artificial Intelligence, PMLR 161:471-481
The complexity of nonconvex-strongly-concave minimax optimization
; Proceedings of the Thirty-Seventh Conference on Uncertainty in Artificial Intelligence, PMLR 161:482-492
High-dimensional Bayesian optimization with sparse axis-aligned subspaces
; Proceedings of the Thirty-Seventh Conference on Uncertainty in Artificial Intelligence, PMLR 161:493-503
Known unknowns: Learning novel concepts using reasoning-by-elimination
; Proceedings of the Thirty-Seventh Conference on Uncertainty in Artificial Intelligence, PMLR 161:504-514
Dynamic visualization for L1 fusion convex clustering in near-linear time
; Proceedings of the Thirty-Seventh Conference on Uncertainty in Artificial Intelligence, PMLR 161:515-524
FlexAE: flexibly learning latent priors for wasserstein auto-encoders
; Proceedings of the Thirty-Seventh Conference on Uncertainty in Artificial Intelligence, PMLR 161:525-535
Generalized parametric path problems
; Proceedings of the Thirty-Seventh Conference on Uncertainty in Artificial Intelligence, PMLR 161:536-546
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Efficient greedy coordinate descent via variable partitioning
; Proceedings of the Thirty-Seventh Conference on Uncertainty in Artificial Intelligence, PMLR 161:547-557
Bayesian streaming sparse Tucker decomposition
; Proceedings of the Thirty-Seventh Conference on Uncertainty in Artificial Intelligence, PMLR 161:558-567
A Nonmyopic Approach to Cost-Constrained Bayesian Optimization
; Proceedings of the Thirty-Seventh Conference on Uncertainty in Artificial Intelligence, PMLR 161:568-577
Asynchronous $ε$-Greedy Bayesian Optimisation
; Proceedings of the Thirty-Seventh Conference on Uncertainty in Artificial Intelligence, PMLR 161:578-588
Global explanations with decision rules: a co-learning approach
; Proceedings of the Thirty-Seventh Conference on Uncertainty in Artificial Intelligence, PMLR 161:589-599
Addressing fairness in classification with a model-agnostic multi-objective algorithm
; Proceedings of the Thirty-Seventh Conference on Uncertainty in Artificial Intelligence, PMLR 161:600-609
A unifying framework for observer-aware planning and its complexity
; Proceedings of the Thirty-Seventh Conference on Uncertainty in Artificial Intelligence, PMLR 161:610-620
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A heuristic for statistical seriation
; Proceedings of the Thirty-Seventh Conference on Uncertainty in Artificial Intelligence, PMLR 161:621-631
LocalNewton: Reducing communication rounds for distributed learning
; Proceedings of the Thirty-Seventh Conference on Uncertainty in Artificial Intelligence, PMLR 161:632-642
Generative Archimedean copulas
; Proceedings of the Thirty-Seventh Conference on Uncertainty in Artificial Intelligence, PMLR 161:643-653
Exploring the loss landscape in neural architecture search
; Proceedings of the Thirty-Seventh Conference on Uncertainty in Artificial Intelligence, PMLR 161:654-664
Finite-time theory for momentum Q-learning
; Proceedings of the Thirty-Seventh Conference on Uncertainty in Artificial Intelligence, PMLR 161:665-674
Scaling Hamiltonian Monte Carlo inference for Bayesian neural networks with symmetric splitting
; Proceedings of the Thirty-Seventh Conference on Uncertainty in Artificial Intelligence, PMLR 161:675-685
Robust principal component analysis for generalized multi-view models
; Proceedings of the Thirty-Seventh Conference on Uncertainty in Artificial Intelligence, PMLR 161:686-695
Decentralized multi-agent active search for sparse signals
; Proceedings of the Thirty-Seventh Conference on Uncertainty in Artificial Intelligence, PMLR 161:696-706
Unbiased gradient estimation for variational auto-encoders using coupled Markov chains
; Proceedings of the Thirty-Seventh Conference on Uncertainty in Artificial Intelligence, PMLR 161:707-717
Possibilistic preference elicitation by minimax regret
; Proceedings of the Thirty-Seventh Conference on Uncertainty in Artificial Intelligence, PMLR 161:718-727
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When is particle filtering efficient for planning in partially observed linear dynamical systems?
; Proceedings of the Thirty-Seventh Conference on Uncertainty in Artificial Intelligence, PMLR 161:728-737
Thompson sampling for Markov games with piecewise stationary opponent policies
; Proceedings of the Thirty-Seventh Conference on Uncertainty in Artificial Intelligence, PMLR 161:738-748
Hierarchical Indian buffet neural networks for Bayesian continual learning
; Proceedings of the Thirty-Seventh Conference on Uncertainty in Artificial Intelligence, PMLR 161:749-759
Measuring data leakage in machine-learning models with Fisher information
; Proceedings of the Thirty-Seventh Conference on Uncertainty in Artificial Intelligence, PMLR 161:760-770
Improved generalization bounds of group invariant / equivariant deep networks via quotient feature spaces
; Proceedings of the Thirty-Seventh Conference on Uncertainty in Artificial Intelligence, PMLR 161:771-780
Probabilistic task modelling for meta-learning
; Proceedings of the Thirty-Seventh Conference on Uncertainty in Artificial Intelligence, PMLR 161:781-791
Approximation algorithm for submodular maximization under submodular cover
; Proceedings of the Thirty-Seventh Conference on Uncertainty in Artificial Intelligence, PMLR 161:792-801
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Tighter Generalization Bounds for Iterative Differentially Private Learning Algorithms
; Proceedings of the Thirty-Seventh Conference on Uncertainty in Artificial Intelligence, PMLR 161:802-812
Dependency in DAG models with hidden variables
; Proceedings of the Thirty-Seventh Conference on Uncertainty in Artificial Intelligence, PMLR 161:813-822
Natural language adversarial defense through synonym encoding
; Proceedings of the Thirty-Seventh Conference on Uncertainty in Artificial Intelligence, PMLR 161:823-833
Path-BN: Towards effective batch normalization in the Path Space for ReLU networks
; Proceedings of the Thirty-Seventh Conference on Uncertainty in Artificial Intelligence, PMLR 161:834-843
Distribution-free uncertainty quantification for classification under label shift
; Proceedings of the Thirty-Seventh Conference on Uncertainty in Artificial Intelligence, PMLR 161:844-853
Identifying untrustworthy predictions in neural networks by geometric gradient analysis
; Proceedings of the Thirty-Seventh Conference on Uncertainty in Artificial Intelligence, PMLR 161:854-864
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Combinatorial semi-bandit in the non-stationary environment
; Proceedings of the Thirty-Seventh Conference on Uncertainty in Artificial Intelligence, PMLR 161:865-875
Time-variant variational transfer for value functions
; Proceedings of the Thirty-Seventh Conference on Uncertainty in Artificial Intelligence, PMLR 161:876-886
BayLIME: Bayesian local interpretable model-agnostic explanations
; Proceedings of the Thirty-Seventh Conference on Uncertainty in Artificial Intelligence, PMLR 161:887-896
On random kernels of residual architectures
; Proceedings of the Thirty-Seventh Conference on Uncertainty in Artificial Intelligence, PMLR 161:897-907
Neural markov logic networks
; Proceedings of the Thirty-Seventh Conference on Uncertainty in Artificial Intelligence, PMLR 161:908-917
Deep kernels with probabilistic embeddings for small-data learning
; Proceedings of the Thirty-Seventh Conference on Uncertainty in Artificial Intelligence, PMLR 161:918-928
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On the effects of quantisation on model uncertainty in Bayesian neural networks
; Proceedings of the Thirty-Seventh Conference on Uncertainty in Artificial Intelligence, PMLR 161:929-938
GP-ConvCNP: Better generalization for conditional convolutional Neural Processes on time series data
; Proceedings of the Thirty-Seventh Conference on Uncertainty in Artificial Intelligence, PMLR 161:939-949
Mixed variable Bayesian optimization with frequency modulated kernels
; Proceedings of the Thirty-Seventh Conference on Uncertainty in Artificial Intelligence, PMLR 161:950-960
Subseasonal climate prediction in the western US using Bayesian spatial models
; Proceedings of the Thirty-Seventh Conference on Uncertainty in Artificial Intelligence, PMLR 161:961-970
variational combinatorial sequential monte carlo methods for bayesian phylogenetic inference
; Proceedings of the Thirty-Seventh Conference on Uncertainty in Artificial Intelligence, PMLR 161:971-981
Estimating treatment effects with observed confounders and mediators
; Proceedings of the Thirty-Seventh Conference on Uncertainty in Artificial Intelligence, PMLR 161:982-991
No-regret learning with high-probability in adversarial Markov decision processes
; Proceedings of the Thirty-Seventh Conference on Uncertainty in Artificial Intelligence, PMLR 161:992-1001
A decentralized policy gradient approach to multi-task reinforcement learning
; Proceedings of the Thirty-Seventh Conference on Uncertainty in Artificial Intelligence, PMLR 161:1002-1012
Compositional abstraction error and a category of causal models
; Proceedings of the Thirty-Seventh Conference on Uncertainty in Artificial Intelligence, PMLR 161:1013-1023
Bayesian optimization for modular black-box systems with switching costs
; Proceedings of the Thirty-Seventh Conference on Uncertainty in Artificial Intelligence, PMLR 161:1024-1034
Probabilistic selection of inducing points in sparse Gaussian processes
; Proceedings of the Thirty-Seventh Conference on Uncertainty in Artificial Intelligence, PMLR 161:1035-1044
Entropic Inequality Constraints from e-separation Relations in Directed Acyclic Graphs with Hidden Variables
; Proceedings of the Thirty-Seventh Conference on Uncertainty in Artificial Intelligence, PMLR 161:1045-1055
Learning proposals for probabilistic programs with inference combinators
; Proceedings of the Thirty-Seventh Conference on Uncertainty in Artificial Intelligence, PMLR 161:1056-1066
Hierarchical infinite relational model
; Proceedings of the Thirty-Seventh Conference on Uncertainty in Artificial Intelligence, PMLR 161:1067-1077
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Unsupervised constrained community detection via self-expressive graph neural network
; Proceedings of the Thirty-Seventh Conference on Uncertainty in Artificial Intelligence, PMLR 161:1078-1088
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NP-DRAW: A Non-Parametric Structured Latent Variable Model for Image Generation
; Proceedings of the Thirty-Seventh Conference on Uncertainty in Artificial Intelligence, PMLR 161:1089-1099
PALM: Probabilistic area loss Minimization for Protein Sequence Alignment
; Proceedings of the Thirty-Seventh Conference on Uncertainty in Artificial Intelligence, PMLR 161:1100-1109
Principal component analysis in the stochastic differential privacy model
; Proceedings of the Thirty-Seventh Conference on Uncertainty in Artificial Intelligence, PMLR 161:1110-1119
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Variance-dependent best arm identification
; Proceedings of the Thirty-Seventh Conference on Uncertainty in Artificial Intelligence, PMLR 161:1120-1129
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Stochastic continuous normalizing flows: training SDEs as ODEs
; Proceedings of the Thirty-Seventh Conference on Uncertainty in Artificial Intelligence, PMLR 161:1130-1140
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On the distribution of penultimate activations of classification networks
; Proceedings of the Thirty-Seventh Conference on Uncertainty in Artificial Intelligence, PMLR 161:1141-1151
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Faster Convergence of Stochastic Gradient Langevin Dynamics for Non-Log-Concave Sampling
; Proceedings of the Thirty-Seventh Conference on Uncertainty in Artificial Intelligence, PMLR 161:1152-1162
Tractable computation of expected kernels
; Proceedings of the Thirty-Seventh Conference on Uncertainty in Artificial Intelligence, PMLR 161:1163-1173
Sparse linear networks with a fixed butterfly structure: theory and practice
; Proceedings of the Thirty-Seventh Conference on Uncertainty in Artificial Intelligence, PMLR 161:1174-1184
Uncertainty-aware sensitivity analysis using Rényi divergences
; Proceedings of the Thirty-Seventh Conference on Uncertainty in Artificial Intelligence, PMLR 161:1185-1194
Testification of Condorcet Winners in dueling bandits
; Proceedings of the Thirty-Seventh Conference on Uncertainty in Artificial Intelligence, PMLR 161:1195-1205
The promises and pitfalls of deep kernel learning
; Proceedings of the Thirty-Seventh Conference on Uncertainty in Artificial Intelligence, PMLR 161:1206-1216
Confidence in causal discovery with linear causal models
; Proceedings of the Thirty-Seventh Conference on Uncertainty in Artificial Intelligence, PMLR 161:1217-1226
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Classification with abstention but without disparities
; Proceedings of the Thirty-Seventh Conference on Uncertainty in Artificial Intelligence, PMLR 161:1227-1236
Maximal ancestral graph structure learning via exact search
; Proceedings of the Thirty-Seventh Conference on Uncertainty in Artificial Intelligence, PMLR 161:1237-1247
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Extendability of causal graphical models: Algorithms and computational complexity
; Proceedings of the Thirty-Seventh Conference on Uncertainty in Artificial Intelligence, PMLR 161:1248-1257
Gaussian process nowcasting: application to COVID-19 mortality reporting
; Proceedings of the Thirty-Seventh Conference on Uncertainty in Artificial Intelligence, PMLR 161:1258-1268
Trumpets: Injective flows for inference and inverse problems
; Proceedings of the Thirty-Seventh Conference on Uncertainty in Artificial Intelligence, PMLR 161:1269-1278
Stochastic model for sunk cost bias
; Proceedings of the Thirty-Seventh Conference on Uncertainty in Artificial Intelligence, PMLR 161:1279-1288
Optimized auxiliary particle filters: adapting mixture proposals via convex optimization
; Proceedings of the Thirty-Seventh Conference on Uncertainty in Artificial Intelligence, PMLR 161:1289-1299
Inference of causal effects when control variables are unknown
; Proceedings of the Thirty-Seventh Conference on Uncertainty in Artificial Intelligence, PMLR 161:1300-1309
Dimension reduction for data with heterogeneous missingness
; Proceedings of the Thirty-Seventh Conference on Uncertainty in Artificial Intelligence, PMLR 161:1310-1320
Tensor-train density estimation
; Proceedings of the Thirty-Seventh Conference on Uncertainty in Artificial Intelligence, PMLR 161:1321-1331
Similarity measure for sparse time course data based on Gaussian processes
; Proceedings of the Thirty-Seventh Conference on Uncertainty in Artificial Intelligence, PMLR 161:1332-1341
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Towards robust episodic meta-learning
; Proceedings of the Thirty-Seventh Conference on Uncertainty in Artificial Intelligence, PMLR 161:1342-1351
ReZero is all you need: fast convergence at large depth
; Proceedings of the Thirty-Seventh Conference on Uncertainty in Artificial Intelligence, PMLR 161:1352-1361
Subset-of-data variational inference for deep Gaussian-processes regression
; Proceedings of the Thirty-Seventh Conference on Uncertainty in Artificial Intelligence, PMLR 161:1362-1370
PLSO: A generative framework for decomposing nonstationary time-series into piecewise stationary oscillatory components
; Proceedings of the Thirty-Seventh Conference on Uncertainty in Artificial Intelligence, PMLR 161:1371-1381
Local explanations via necessity and sufficiency: unifying theory and practice
; Proceedings of the Thirty-Seventh Conference on Uncertainty in Artificial Intelligence, PMLR 161:1382-1392
Faster lifting for two-variable logic using cell graphs
; Proceedings of the Thirty-Seventh Conference on Uncertainty in Artificial Intelligence, PMLR 161:1393-1402
Post-hoc loss-calibration for Bayesian neural networks
; Proceedings of the Thirty-Seventh Conference on Uncertainty in Artificial Intelligence, PMLR 161:1403-1412
Towards tractable optimism in model-based reinforcement learning
; Proceedings of the Thirty-Seventh Conference on Uncertainty in Artificial Intelligence, PMLR 161:1413-1423
Probabilistic DAG search
; Proceedings of the Thirty-Seventh Conference on Uncertainty in Artificial Intelligence, PMLR 161:1424-1433
Causal and interventional Markov boundaries
; Proceedings of the Thirty-Seventh Conference on Uncertainty in Artificial Intelligence, PMLR 161:1434-1443
Simple combinatorial algorithms for combinatorial bandits: corruptions and approximations
; Proceedings of the Thirty-Seventh Conference on Uncertainty in Artificial Intelligence, PMLR 161:1444-1454
CLAIM: curriculum learning policy for influence maximization in unknown social networks
; Proceedings of the Thirty-Seventh Conference on Uncertainty in Artificial Intelligence, PMLR 161:1455-1465
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Learning to learn with Gaussian processes
; Proceedings of the Thirty-Seventh Conference on Uncertainty in Artificial Intelligence, PMLR 161:1466-1475
Sum-product laws and efficient algorithms for imprecise Markov chains
; Proceedings of the Thirty-Seventh Conference on Uncertainty in Artificial Intelligence, PMLR 161:1476-1485
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Trusted-maximizers entropy search for efficient Bayesian optimization
; Proceedings of the Thirty-Seventh Conference on Uncertainty in Artificial Intelligence, PMLR 161:1486-1495
Minimax sample complexity for turn-based stochastic game
; Proceedings of the Thirty-Seventh Conference on Uncertainty in Artificial Intelligence, PMLR 161:1496-1504
Multi-output Gaussian Processes for uncertainty-aware recommender systems
; Proceedings of the Thirty-Seventh Conference on Uncertainty in Artificial Intelligence, PMLR 161:1505-1514
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Generalization error bounds for deep unfolding RNNs
; Proceedings of the Thirty-Seventh Conference on Uncertainty in Artificial Intelligence, PMLR 161:1515-1524
RISAN: Robust instance specific deep abstention network
; Proceedings of the Thirty-Seventh Conference on Uncertainty in Artificial Intelligence, PMLR 161:1525-1534
Contingency-aware influence maximization: A reinforcement learning approach
; Proceedings of the Thirty-Seventh Conference on Uncertainty in Artificial Intelligence, PMLR 161:1535-1545
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Invariant representation learning for treatment effect estimation
; Proceedings of the Thirty-Seventh Conference on Uncertainty in Artificial Intelligence, PMLR 161:1546-1555
Generating adversarial examples with graph neural networks
; Proceedings of the Thirty-Seventh Conference on Uncertainty in Artificial Intelligence, PMLR 161:1556-1564
A Bayesian nonparametric conditional two-sample test with an application to Local Causal Discovery
; Proceedings of the Thirty-Seventh Conference on Uncertainty in Artificial Intelligence, PMLR 161:1565-1575
Graph-based semi-supervised learning through the lens of safety
; Proceedings of the Thirty-Seventh Conference on Uncertainty in Artificial Intelligence, PMLR 161:1576-1586
Strategically efficient exploration in competitive multi-agent reinforcement learning
; Proceedings of the Thirty-Seventh Conference on Uncertainty in Artificial Intelligence, PMLR 161:1587-1596
Information theoretic meta learning with Gaussian processes
; Proceedings of the Thirty-Seventh Conference on Uncertainty in Artificial Intelligence, PMLR 161:1597-1606
Combining pseudo-point and state space approximations for sum-separable Gaussian Processes
; Proceedings of the Thirty-Seventh Conference on Uncertainty in Artificial Intelligence, PMLR 161:1607-1617
Class balancing GAN with a classifier in the loop
; Proceedings of the Thirty-Seventh Conference on Uncertainty in Artificial Intelligence, PMLR 161:1618-1627
Hierarchical learning of Hidden Markov Models with clustering regularization
; Proceedings of the Thirty-Seventh Conference on Uncertainty in Artificial Intelligence, PMLR 161:1628-1638
Enabling long-range exploration in minimization of multimodal functions
; Proceedings of the Thirty-Seventh Conference on Uncertainty in Artificial Intelligence, PMLR 161:1639-1649
An optimization and generalization analysis for max-pooling networks
; Proceedings of the Thirty-Seventh Conference on Uncertainty in Artificial Intelligence, PMLR 161:1650-1660
Investigating vulnerabilities of deep neural policies
; Proceedings of the Thirty-Seventh Conference on Uncertainty in Artificial Intelligence, PMLR 161:1661-1670
Modeling financial uncertainty with multivariate temporal entropy-based curriculums
; Proceedings of the Thirty-Seventh Conference on Uncertainty in Artificial Intelligence, PMLR 161:1671-1681
Random probabilistic circuits
; Proceedings of the Thirty-Seventh Conference on Uncertainty in Artificial Intelligence, PMLR 161:1682-1691
Multi-task and meta-learning with sparse linear bandits
; Proceedings of the Thirty-Seventh Conference on Uncertainty in Artificial Intelligence, PMLR 161:1692-1702
Federated stochastic gradient Langevin dynamics
; Proceedings of the Thirty-Seventh Conference on Uncertainty in Artificial Intelligence, PMLR 161:1703-1712
Certification of iterative predictions in Bayesian neural networks
; Proceedings of the Thirty-Seventh Conference on Uncertainty in Artificial Intelligence, PMLR 161:1713-1723
Integer programming-based error-correcting output code design for robust classification
; Proceedings of the Thirty-Seventh Conference on Uncertainty in Artificial Intelligence, PMLR 161:1724-1734
Statistically robust neural network classification
; Proceedings of the Thirty-Seventh Conference on Uncertainty in Artificial Intelligence, PMLR 161:1735-1745
Markov equivalence of max-linear Bayesian networks
; Proceedings of the Thirty-Seventh Conference on Uncertainty in Artificial Intelligence, PMLR 161:1746-1755
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Constrained differentially private federated learning for low-bandwidth devices
; Proceedings of the Thirty-Seventh Conference on Uncertainty in Artificial Intelligence, PMLR 161:1756-1765
Know your limits: Uncertainty estimation with ReLU classifiers fails at reliable OOD detection
; Proceedings of the Thirty-Seventh Conference on Uncertainty in Artificial Intelligence, PMLR 161:1766-1776
Nearest neighbor search under uncertainty
; Proceedings of the Thirty-Seventh Conference on Uncertainty in Artificial Intelligence, PMLR 161:1777-1786
Contextual policy transfer in reinforcement learning domains via deep mixtures-of-experts
; Proceedings of the Thirty-Seventh Conference on Uncertainty in Artificial Intelligence, PMLR 161:1787-1797
Partial Identifiability in Discrete Data with Measurement Error
; Proceedings of the Thirty-Seventh Conference on Uncertainty in Artificial Intelligence, PMLR 161:1798-1808
Bias-corrected peaks-over-threshold estimation of the CVaR
; Proceedings of the Thirty-Seventh Conference on Uncertainty in Artificial Intelligence, PMLR 161:1809-1818
Variational refinement for importance sampling using the forward Kullback-Leibler divergence
; Proceedings of the Thirty-Seventh Conference on Uncertainty in Artificial Intelligence, PMLR 161:1819-1829
Diagnostics for conditional density models and Bayesian inference algorithms
; Proceedings of the Thirty-Seventh Conference on Uncertainty in Artificial Intelligence, PMLR 161:1830-1840
Non-PSD matrix sketching with applications to regression and optimization
; Proceedings of the Thirty-Seventh Conference on Uncertainty in Artificial Intelligence, PMLR 161:1841-1851
Staying in shape: learning invariant shape representations using contrastive learning
; Proceedings of the Thirty-Seventh Conference on Uncertainty in Artificial Intelligence, PMLR 161:1852-1862
Convergence behavior of belief propagation: estimating regions of attraction via Lyapunov functions
; Proceedings of the Thirty-Seventh Conference on Uncertainty in Artificial Intelligence, PMLR 161:1863-1873
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Explaining fast improvement in online imitation learning
; Proceedings of the Thirty-Seventh Conference on Uncertainty in Artificial Intelligence, PMLR 161:1874-1884
Gradient-based optimization for multi-resource spatial coverage problems
; Proceedings of the Thirty-Seventh Conference on Uncertainty in Artificial Intelligence, PMLR 161:1885-1894
Doubly non-central beta matrix factorization for DNA methylation data
; Proceedings of the Thirty-Seventh Conference on Uncertainty in Artificial Intelligence, PMLR 161:1895-1904
SGD with low-dimensional gradients with applications to private and distributed learning
; Proceedings of the Thirty-Seventh Conference on Uncertainty in Artificial Intelligence, PMLR 161:1905-1915
Active multi-fidelity Bayesian online changepoint detection
; Proceedings of the Thirty-Seventh Conference on Uncertainty in Artificial Intelligence, PMLR 161:1916-1926
Learning in Multi-Player Stochastic Games
; Proceedings of the Thirty-Seventh Conference on Uncertainty in Artificial Intelligence, PMLR 161:1927-1937
q-Paths: Generalizing the geometric annealing path using power means
; Proceedings of the Thirty-Seventh Conference on Uncertainty in Artificial Intelligence, PMLR 161:1938-1947
Condition number bounds for causal inference
; Proceedings of the Thirty-Seventh Conference on Uncertainty in Artificial Intelligence, PMLR 161:1948-1957
Sketching curvature for efficient out-of-distribution detection for deep neural networks
; Proceedings of the Thirty-Seventh Conference on Uncertainty in Artificial Intelligence, PMLR 161:1958-1967
CORe: Capitalizing On Rewards in Bandit Exploration
; Proceedings of the Thirty-Seventh Conference on Uncertainty in Artificial Intelligence, PMLR 161:1968-1978
Explicit pairwise factorized graph neural network for semi-supervised node classification
; Proceedings of the Thirty-Seventh Conference on Uncertainty in Artificial Intelligence, PMLR 161:1979-1987
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Statistical mechanical analysis of neural network pruning
; Proceedings of the Thirty-Seventh Conference on Uncertainty in Artificial Intelligence, PMLR 161:1988-1997
Correlated weights in infinite limits of deep convolutional neural networks
; Proceedings of the Thirty-Seventh Conference on Uncertainty in Artificial Intelligence, PMLR 161:1998-2007
Leveraging probabilistic circuits for nonparametric multi-output regression
; Proceedings of the Thirty-Seventh Conference on Uncertainty in Artificial Intelligence, PMLR 161:2008-2018
PROVIDE: a probabilistic framework for unsupervised video decomposition
; Proceedings of the Thirty-Seventh Conference on Uncertainty in Artificial Intelligence, PMLR 161:2019-2028
Uncertainty in minimum cost multicuts for image and motion segmentation
; Proceedings of the Thirty-Seventh Conference on Uncertainty in Artificial Intelligence, PMLR 161:2029-2038
Learning probabilistic sentential decision diagrams under logic constraints by sampling and averaging
; Proceedings of the Thirty-Seventh Conference on Uncertainty in Artificial Intelligence, PMLR 161:2039-2049
Conditionally independent data generation
; Proceedings of the Thirty-Seventh Conference on Uncertainty in Artificial Intelligence, PMLR 161:2050-2060
Exact and approximate hierarchical clustering using A*
; Proceedings of the Thirty-Seventh Conference on Uncertainty in Artificial Intelligence, PMLR 161:2061-2071
Efficient online inference for nonparametric mixture models
; Proceedings of the Thirty-Seventh Conference on Uncertainty in Artificial Intelligence, PMLR 161:2072-2081
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No-regret approximate inference via Bayesian optimisation
; Proceedings of the Thirty-Seventh Conference on Uncertainty in Artificial Intelligence, PMLR 161:2082-2092
Disentangling mixtures of unknown causal interventions
; Proceedings of the Thirty-Seventh Conference on Uncertainty in Artificial Intelligence, PMLR 161:2093-2102
SDM-Net: A simple and effective model for generalized zero-shot learning
; Proceedings of the Thirty-Seventh Conference on Uncertainty in Artificial Intelligence, PMLR 161:2103-2113
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Towards a unified framework for fair and stable graph representation learning
; Proceedings of the Thirty-Seventh Conference on Uncertainty in Artificial Intelligence, PMLR 161:2114-2124
Identifying regions of trusted predictions
; Proceedings of the Thirty-Seventh Conference on Uncertainty in Artificial Intelligence, PMLR 161:2125-2134
Learning and certification under instance-targeted poisoning
; Proceedings of the Thirty-Seventh Conference on Uncertainty in Artificial Intelligence, PMLR 161:2135-2145
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Min/max stability and box distributions
; Proceedings of the Thirty-Seventh Conference on Uncertainty in Artificial Intelligence, PMLR 161:2146-2155
Geometric rates of convergence for kernel-based sampling algorithms
; Proceedings of the Thirty-Seventh Conference on Uncertainty in Artificial Intelligence, PMLR 161:2156-2164
Sequential core-set Monte Carlo
; Proceedings of the Thirty-Seventh Conference on Uncertainty in Artificial Intelligence, PMLR 161:2165-2175
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