pac learning

Superconstant Inapproximability of Decision Tree Learning COLT 2024 The sample complexity of multi-distribution learning COLT 2024 Towards the Transferability of Rewards Recovered via Regularized Inverse Reinforcement Learning NeurIPS 2024 Transductive Learning is Compact NeurIPS 2024 Universal Rates for Active Learning NeurIPS 2024 Universal Rates of Empirical Risk Minimization NeurIPS 2024 ε-fractional core stability in Hedonic Games. NeurIPS 2023 Active Bipartite Ranking NeurIPS 2023 Adversarially Robust PAC Learnability of Real-Valued Functions ICML 2023 Agnostic Multi-Group Active Learning NeurIPS 2023 Agnostic PAC Learning of k-juntas Using L_2-Polynomial Regression AISTATS 2023 A Parameterized Theory of PAC Learning AAAI 2023 Asymptotically Optimal Quantile Pure Exploration for Infinite-Armed Bandits NeurIPS 2023 Attribute-Efficient PAC Learning of Low-Degree Polynomial Threshold Functions with Nasty Noise ICML 2023 Bagging is an Optimal PAC Learner COLT 2023 Bandit Learnability can be Undecidable COLT 2023 Breaking a Classical Barrier for Classifying Arbitrary Test Examples in the Quantum Model AISTATS 2023 Context-lumpable stochastic bandits NeurIPS 2023 Fine-Grained Distribution-Dependent Learning Curves COLT 2023 Information-Computation Tradeoffs for Learning Margin Halfspaces with Random Classification Noise COLT 2023 List and Certificate Complexities in Replicable Learning NeurIPS 2023 Lower Bounds for Learning in Revealing POMDPs ICML 2023 Multiclass Boosting: Simple and Intuitive Weak Learning Criteria NeurIPS 2023 On the Complexity of PAC Learning in Hilbert Spaces AAAI 2023 On the Role of Entanglement and Statistics in Learning NeurIPS 2023