sample complexity

On the Sample Complexity of Representation Learning in Multi-Task Bandits with Global and Local Structure AAAI 2023 On the Sample Complexity of Vanilla Model-Based Offline Reinforcement Learning with Dependent Samples AAAI 2023 Open problem: log(n) factor in "Local Glivenko-Cantelli" COLT 2023 Open Problem: The Sample Complexity of Multi-Distribution Learning for VC Classes COLT 2023 Optimal Convergence Rate for Exact Policy Mirror Descent in Discounted Markov Decision Processes NeurIPS 2023 Optimal Excess Risk Bounds for Empirical Risk Minimization on p-Norm Linear Regression NeurIPS 2023 Optimal Horizon-Free Reward-Free Exploration for Linear Mixture MDPs ICML 2023 Optimally-weighted Estimators of the Maximum Mean Discrepancy for Likelihood-Free Inference ICML 2023 Optimal Sample Complexity Bounds for Non-convex Optimization under Kurdyka-Lojasiewicz Condition AISTATS 2023 Optimistic Exploration with Learned Features Provably Solves Markov Decision Processes with Neural Dynamics ICLR 2023 Optimistic Natural Policy Gradient: a Simple Efficient Policy Optimization Framework for Online RL NeurIPS 2023 Optimistic PAC Reinforcement Learning: the Instance-Dependent View ALT 2023 Oracle-free Reinforcement Learning in Mean-Field Games along a Single Sample Path AISTATS 2023 PAC Learning of Halfspaces with Malicious Noise in Nearly Linear Time AISTATS 2023 PAC Reinforcement Learning for Predictive State Representations ICLR 2023 Partially Observable RL with B-Stability: Unified Structural Condition and Sharp Sample-Efficient Algorithms ICLR 2023 Patch-level Routing in Mixture-of-Experts is Provably Sample-efficient for Convolutional Neural Networks ICML 2023 Policy Mirror Ascent for Efficient and Independent Learning in Mean Field Games ICML 2023 Polynomial Time and Private Learning of Unbounded Gaussian Mixture Models ICML 2023 Probabilistic Invariant Learning with Randomized Linear Classifiers NeurIPS 2023 Prometheus: Taming Sample and Communication Complexities in Constrained Decentralized Stochastic Bilevel Learning ICML 2023 Promises and Pitfalls of Threshold-based Auto-labeling NeurIPS 2023 Provable Benefit of Mixup for Finding Optimal Decision Boundaries ICML 2023 Provable Benefits of Representational Transfer in Reinforcement Learning COLT 2023 Provable Guarantees for Nonlinear Feature Learning in Three-Layer Neural Networks NeurIPS 2023