sample complexity

Open Problem: Can Local Regularization Learn All Multiclass Problems? COLT 2024 Open problem: Direct Sums in Learning Theory COLT 2024 Open Problem: Tight Characterization of Instance-Optimal Identity Testing COLT 2024 Optimal Algorithms for Augmented Testing of Discrete Distributions NeurIPS 2024 Optimal Batched Best Arm Identification NeurIPS 2024 Optimal Clustering with Bandit Feedback JMLR 2024 Optimal Multi-Distribution Learning COLT 2024 Optimal Multi-Fidelity Best-Arm Identification NeurIPS 2024 Optimal Sample Complexity for Average Reward Markov Decision Processes ICLR 2024 Optimal Sample Complexity of Contrastive Learning ICLR 2024 Optimal Top-Two Method for Best Arm Identification and Fluid Analysis NeurIPS 2024 Optimistic Rates for Learning from Label Proportions COLT 2024 Oracle-Efficient Differentially Private Learning with Public Data NeurIPS 2024 Overcoming the Sim-to-Real Gap: Leveraging Simulation to Learn to Explore for Real-World RL NeurIPS 2024 PARL: A Unified Framework for Policy Alignment in Reinforcement Learning from Human Feedback ICLR 2024 Performative Reinforcement Learning in Gradually Shifting Environments UAI 2024 PILOT: An O(1/K)-Convergent Approach for Policy Evaluation with Nonlinear Function Approximation ICLR 2024 Policy Evaluation for Reinforcement Learning from Human Feedback: A Sample Complexity Analysis AISTATS 2024 Policy Mirror Descent with Lookahead NeurIPS 2024 Predicting Ground State Properties: Constant Sample Complexity and Deep Learning Algorithms NeurIPS 2024 Preference-based Pure Exploration NeurIPS 2024 Principal eigenstate classical shadows COLT 2024 Private Gradient Descent for Linear Regression: Tighter Error Bounds and Instance-Specific Uncertainty Estimation ICML 2024 Private Truly-Everlasting Robust-Prediction ICML 2024 Projection by Convolution: Optimal Sample Complexity for Reinforcement Learning in Continuous-Space MDPs COLT 2024