sample complexity

Thinking Outside the Ball: Optimal Learning with Gradient Descent for Generalized Linear Stochastic Convex Optimization NeurIPS 2022 Towards Bridging Sample Complexity and Model Capacity AAAI 2022 Towards General Function Approximation in Zero-Sum Markov Games ICLR 2022 Towards Statistical and Computational Complexities of Polyak Step Size Gradient Descent AISTATS 2022 Transfer Learning In Differential Privacy’s Hybrid-Model ICML 2022 TURF: Two-Factor, Universal, Robust, Fast Distribution Learning Algorithm ICML 2022 Two-Sample Testing on Ranked Preference Data and the Role of Modeling Assumptions JMLR 2022 Unpacking Reward Shaping: Understanding the Benefits of Reward Engineering on Sample Complexity NeurIPS 2022 When are Offline Two-Player Zero-Sum Markov Games Solvable? NeurIPS 2022 When Can We Learn General-Sum Markov Games with a Large Number of Players Sample-Efficiently? ICLR 2022 When Is Partially Observable Reinforcement Learning Not Scary? COLT 2022 Active Learning under Label Shift AISTATS 2021 Adaptive Reward-Free Exploration ALT 2021 Adaptive Sampling for Best Policy Identification in Markov Decision Processes ICML 2021 A Dimension-free Computational Upper-bound for Smooth Optimal Transport Estimation COLT 2021 Adversarially Robust Learning with Unknown Perturbation Sets COLT 2021 Aggregating Incomplete and Noisy Rankings AISTATS 2021 Agnostic Reinforcement Learning with Low-Rank MDPs and Rich Observations NeurIPS 2021 A Lower Bound for the Sample Complexity of Inverse Reinforcement Learning ICML 2021 A Mathematical Framework for Quantifying Transferability in Multi-source Transfer Learning NeurIPS 2021 An Exponential Lower Bound for Linearly Realizable MDP with Constant Suboptimality Gap NeurIPS 2021 A Provably Efficient Sample Collection Strategy for Reinforcement Learning NeurIPS 2021 A Regression Approach to Learning-Augmented Online Algorithms NeurIPS 2021 A Sharp Analysis of Model-based Reinforcement Learning with Self-Play ICML 2021 A Theoretical Analysis of Fine-tuning with Linear Teachers NeurIPS 2021