Learning Theory

Attribute-Efficient PAC Learning of Low-Degree Polynomial Threshold Functions with Nasty Noise ICML 2023 A Unified Algorithm for Stochastic Path Problems ALT 2023 A Unified Approach to Domain Incremental Learning with Memory: Theory and Algorithm NeurIPS 2023 A Unified Detection Framework for Inference-Stage Backdoor Defenses NeurIPS 2023 A Unified Experiment Design Approach for Cyclic and Acyclic Causal Models JMLR 2023 A unified framework for information-theoretic generalization bounds NeurIPS 2023 A Unified Generalization Analysis of Re-Weighting and Logit-Adjustment for Imbalanced Learning NeurIPS 2023 A Unified Model and Dimension for Interactive Estimation NeurIPS 2023 A Unified Recipe for Deriving (Time-Uniform) PAC-Bayes Bounds JMLR 2023 A Unified Theory of Diversity in Ensemble Learning JMLR 2023 Automata Cascades: Expressivity and Sample Complexity AAAI 2023 Autonomous Exploration for Navigating in MDPs Using Blackbox RL Algorithms IJCAI 2023 A U-turn on Double Descent: Rethinking Parameter Counting in Statistical Learning NeurIPS 2023 Average Sensitivity of Decision Tree Learning ICLR 2023 Backpropagation at the Infinitesimal Inference Limit of Energy-Based Models: Unifying Predictive Coding, Equilibrium Propagation, and Contrastive Hebbian Learning ICLR 2023 Backstepping Temporal Difference Learning ICLR 2023 Backward Feature Correction: How Deep Learning Performs Deep (Hierarchical) Learning COLT 2023 Bagging is an Optimal PAC Learner COLT 2023 Bandit Learnability can be Undecidable COLT 2023 Bandit Submodular Maximization for Multi-Robot Coordination in Unpredictable and Partially Observable Environments RSS 2023 Bandits with Knapsacks: Advice on Time-Varying Demands ICML 2023 Bayesian Structure Scores for Probabilistic Circuits AISTATS 2023 Bayes-optimal Learning of Deep Random Networks of Extensive-width ICML 2023 Benchmarking Long-tail Generalization with Likelihood Splits EACL 2023 Benchmarking Low-Shot Robustness to Natural Distribution Shifts ICCV 2023