sample complexity

Sample Complexity of Uniform Convergence for Multicalibration NeurIPS 2020 Sample Efficient Policy Gradient Methods with Recursive Variance Reduction ICLR 2020 Sample-Efficient Reinforcement Learning of Undercomplete POMDPs NeurIPS 2020 Sample Efficient Reinforcement Learning via Low-Rank Matrix Estimation NeurIPS 2020 Sequential Transfer in Reinforcement Learning with a Generative Model ICML 2020 Sharpened Generalization Bounds based on Conditional Mutual Information and an Application to Noisy, Iterative Algorithms NeurIPS 2020 Solving Discounted Stochastic Two-Player Games with Near-Optimal Time and Sample Complexity AISTATS 2020 Spectral Methods for Ranking with Scarce Data UAI 2020 Statistical Optimal Transport posed as Learning Kernel Embedding NeurIPS 2020 Student Specialization in Deep Rectified Networks With Finite Width and Input Dimension ICML 2020 SURF: A Simple, Universal, Robust, Fast Distribution Learning Algorithm NeurIPS 2020 Testing Determinantal Point Processes NeurIPS 2020 The EM Algorithm gives Sample-Optimality for Learning Mixtures of Well-Separated Gaussians COLT 2020 The Power of Comparisons for Actively Learning Linear Classifiers NeurIPS 2020 The Sample Complexity of Best-k Items Selection from Pairwise Comparisons ICML 2020 The Statistical Cost of Robust Kernel Hyperparameter Turning NeurIPS 2020 The True Sample Complexity of Identifying Good Arms AISTATS 2020 Top-k Combinatorial Bandits with Full-Bandit Feedback ALT 2020 Towards Understanding Hierarchical Learning: Benefits of Neural Representations NeurIPS 2020 Variance-Reduced Off-Policy TDC Learning: Non-Asymptotic Convergence Analysis NeurIPS 2020 What Can Neural Networks Reason About? ICLR 2020 Worst-Case Analysis for Randomly Collected Data NeurIPS 2020 Active Exploration in Markov Decision Processes AISTATS 2019 A General Framework for Symmetric Property Estimation NeurIPS 2019 Algorithmic Framework for Model-based Deep Reinforcement Learning with Theoretical Guarantees ICLR 2019