pac learning

Realizable Learning is All You Need COLT 2022 Reward-Free RL is No Harder Than Reward-Aware RL in Linear Markov Decision Processes ICML 2022 Sample Complexity Bounds for Robustly Learning Decision Lists against Evasion Attacks IJCAI 2022 SQ Lower Bounds for Learning Single Neurons with Massart Noise NeurIPS 2022 The Complexity of Learning Approval-Based Multiwinner Voting Rules AAAI 2022 An Axiomatic Theory of Provably-Fair Welfare-Centric Machine Learning NeurIPS 2021 A Theory of Heuristic Learnability COLT 2021 Boosting in the Presence of Massart Noise COLT 2021 Communication-Aware Collaborative Learning AAAI 2021 Efficiently Learning One Hidden Layer ReLU Networks From Queries NeurIPS 2021 Efficient PAC Reinforcement Learning in Regular Decision Processes IJCAI 2021 Epsilon Best Arm Identification in Spectral Bandits IJCAI 2021 Exponential Separation between Two Learning Models and Adversarial Robustness NeurIPS 2021 Forster Decomposition and Learning Halfspaces with Noise NeurIPS 2021 From Local Pseudorandom Generators to Hardness of Learning COLT 2021 Improved Algorithms for Efficient Active Learning Halfspaces with Massart and Tsybakov Noise COLT 2021 Incentive-Aware PAC Learning AAAI 2021 Learning with Safety Constraints: Sample Complexity of Reinforcement Learning for Constrained MDPs AAAI 2021 Learn to Expect the Unexpected: Probably Approximately Correct Domain Generalization AISTATS 2021 List Learning with Attribute Noise AISTATS 2021 Multiclass Boosting and the Cost of Weak Learning NeurIPS 2021 Multiclass versus Binary Differentially Private PAC Learning NeurIPS 2021 Multi-group Agnostic PAC Learnability ICML 2021 On the Power of Differentiable Learning versus PAC and SQ Learning NeurIPS 2021 PAC Learning of Causal Trees with Latent Variables AAAI 2021