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sample complexity

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reinforcement learning (137) pac learning (117) markov decision process (112) multi-armed bandit (94) learning theory (78) differential privacy (68) best arm identification (64) regret bound (63) stochastic optimization (53) neural network (53)

Papers

Stochastic Safe Action Model Learning COLT 2026 The Role of Contextual Information in Best Arm Identification JMLR 2026 The Sample Complexity of Multiclass and Sparse Contextual Bandits COLT 2026 The Sample Complexity of Parameter-Free Stochastic Convex Optimization JMLR 2026 Tight Sample Complexity Bounds for Entropic Best Policy Identification COLT 2026 Tight Sample Complexity of Transformers COLT 2026 Trajectory Data Suffices for Statistically Efficient Policy Evaluation in Fixed-Horizon Offline RL with Linear q^π-Realizability and Concentrability COLT 2026 Trajectory-Level Experimental Design for Fast Safety Parameter Estimation of Unknown Environments by Autonomous Systems L4DC 2026 Uniform Laws of Large Numbers in Product Spaces COLT 2026 Variance Reduction and Low Sample Complexity in Stochastic Optimization via Proximal Point Method ALT 2026 Wedge Sampling: Efficient Tensor Completion with Nearly-Linear Sample Complexity COLT 2026 When Both Layers Learn: Training Dynamics of Representing Linear Models via ReLU Networks COLT 2026 Accelerating Quantum Reinforcement Learning with a Quantum Natural Policy Gradient Based Approach ICML 2025 A Convex Relaxation Approach to Generalization Analysis for Parallel Positively Homogeneous Networks AISTATS 2025 Active Bipartite Ranking with Smooth Posterior Distributions AISTATS 2025 Active Treatment Effect Estimation via Limited Samples ICML 2025 Actor-Critics Can Achieve Optimal Sample Efficiency ICML 2025 Adaptive Exploration for Multi-Reward Multi-Policy Evaluation ICML 2025 A Distributional-Lifting Theorem for PAC Learning COLT 2025 Adversarial Policy Optimization for Offline Preference-based Reinforcement Learning ICLR 2025 Agnostic Private Density Estimation for GMMs via List Global Stability ALT 2025 Almost Sure Convergence of Dropout Algorithms for Neural Networks JMLR 2025 A Reduction Framework for Distributionally Robust Reinforcement Learning under Average Reward ICML 2025 A Robust Kernel Statistical Test of Invariance: Detecting Subtle Asymmetries AISTATS 2025 A Safe Exploration Approach to Constrained Markov Decision Processes AISTATS 2025