Sample Complexity

The role of randomness in quantum state certification with unentangled measurements COLT 2024 The sample complexity of multi-distribution learning COLT 2024 The Star Number and Eluder Dimension: Elementary Observations About the Dimensions of Disagreement COLT 2024 Towards Minimax Optimality of Model-based Robust Reinforcement Learning UAI 2024 Worst-Case Offline Reinforcement Learning with Arbitrary Data Support NeurIPS 2024 Active Coverage for PAC Reinforcement Learning COLT 2023 A Parameterized Theory of PAC Learning AAAI 2023 A Pretty Fast Algorithm for Adaptive Private Mean Estimation COLT 2023 Bagging is an Optimal PAC Learner COLT 2023 Bandit Learnability can be Undecidable COLT 2023 Complexity of High-Dimensional Identity Testing with Coordinate Conditional Sampling COLT 2023 Computably Continuous Reinforcement-Learning Objectives Are PAC-Learnable AAAI 2023 Efficient median of means estimator COLT 2023 Find a witness or shatter: the landscape of computable PAC learning. COLT 2023 Fine-Grained Distribution-Dependent Learning Curves COLT 2023 Information-Computation Tradeoffs for Learning Margin Halfspaces with Random Classification Noise COLT 2023 KAKURENBO: Adaptively Hiding Samples in Deep Neural Network Training NeurIPS 2023 Learning ReLU networks to high uniform accuracy is intractable ICLR 2023 Learning Revenue Maximization Using Posted Prices for Stochastic Strategic Patient Buyers AAAI 2023 Multi-task Representation Learning for Pure Exploration in Bilinear Bandits NeurIPS 2023 Near-Optimal Deployment Efficiency in Reward-Free Reinforcement Learning with Linear Function Approximation ICLR 2023 On the Existence of a Complexity in Fixed Budget Bandit Identification COLT 2023 On the Global Convergence of Fitted Q-Iteration with Two-layer Neural Network Parametrization ICML 2023 Open Problem: The Sample Complexity of Multi-Distribution Learning for VC Classes COLT 2023 PAC Reinforcement Learning for Predictive State Representations ICLR 2023