sample complexity

A Theoretical Characterization of Semi-supervised Learning with Self-training for Gaussian Mixture Models AISTATS 2021 A theory of high dimensional regression with arbitrary correlations between input features and target functions: sample complexity, multiple descent curves and a hierarchy of phase transitions ICML 2021 Bellman Eluder Dimension: New Rich Classes of RL Problems, and Sample-Efficient Algorithms NeurIPS 2021 Besov Function Approximation and Binary Classification on Low-Dimensional Manifolds Using Convolutional Residual Networks ICML 2021 Bilinear Classes: A Structural Framework for Provable Generalization in RL ICML 2021 Breaking The Dimension Dependence in Sparse Distribution Estimation under Communication Constraints COLT 2021 Breaking the Sample Complexity Barrier to Regret-Optimal Model-Free Reinforcement Learning NeurIPS 2021 Bypassing the Ambient Dimension: Private SGD with Gradient Subspace Identification ICLR 2021 Causal Inference with Selectively Deconfounded Data AISTATS 2021 Cautiously Optimistic Policy Optimization and Exploration with Linear Function Approximation COLT 2021 ChaCha for Online AutoML ICML 2021 C-Learning: Horizon-Aware Cumulative Accessibility Estimation ICLR 2021 Closing the Gap: Tighter Analysis of Alternating Stochastic Gradient Methods for Bilevel Problems NeurIPS 2021 Combinatorial Pure Exploration with Bottleneck Reward Function NeurIPS 2021 Combinatorial Pure Exploration with Full-Bandit or Partial Linear Feedback AAAI 2021 Communication-Aware Collaborative Learning AAAI 2021 Concentric mixtures of Mallows models for top-k rankings: sampling and identifiability ICML 2021 Dealing With Misspecification In Fixed-Confidence Linear Top-m Identification NeurIPS 2021 Derivative-Free Policy Optimization for Linear Risk-Sensitive and Robust Control Design: Implicit Regularization and Sample Complexity NeurIPS 2021 Differentially-Private Clustering of Easy Instances ICML 2021 Discrete-Valued Latent Preference Matrix Estimation with Graph Side Information ICML 2021 Distributed Estimation with Multiple Samples per User: Sharp Rates and Phase Transition NeurIPS 2021 Divergence Frontiers for Generative Models: Sample Complexity, Quantization Effects, and Frontier Integrals NeurIPS 2021 Don’t Do What Doesn’t Matter: Intrinsic Motivation with Action Usefulness IJCAI 2021 Doubly Robust Off-Policy Actor-Critic: Convergence and Optimality ICML 2021