finite sample bound

Finite Sample Bounds for Learning with Score Matching COLT 2026 Offline Multi-Objective Bandits: From Logged Data to Pareto-Optimal Policies AAAI 2026 How good is your Laplace approximation of the Bayesian posterior? Finite-sample computable error bounds for a variety of useful divergences JMLR 2025 Logarithmic Neyman Regret for Adaptive Estimation of the Average Treatment Effect AISTATS 2025 Model-Based Exploration in Monitored Markov Decision Processes ICML 2025 Conformal prediction for multi-dimensional time series by ellipsoidal sets ICML 2024 Compression, Generalization and Learning JMLR 2023 Density Ratio Estimation and Neyman Pearson Classification with Missing Data AISTATS 2023 FARE: Provably Fair Representation Learning with Practical Certificates ICML 2023 Influence Diagnostics under Self-concordance AISTATS 2023 Optimal Sparse Recovery with Decision Stumps AAAI 2023 Bregman Power k-Means for Clustering Exponential Family Data ICML 2022 Optimal Estimation of Policy Gradient via Double Fitted Iteration ICML 2022 Statistical Learning and Inverse Problems: A Stochastic Gradient Approach NeurIPS 2022 Dimension-free empirical entropy estimation NeurIPS 2021 Finite-Sample Analysis of Off-Policy TD-Learning via Generalized Bellman Operators NeurIPS 2021 A Finite-Sample Deviation Bound for Stable Autoregressive Processes L4DC 2020 Black-box Off-policy Estimation for Infinite-Horizon Reinforcement Learning ICLR 2020 Orlicz Random Fourier Features JMLR 2020 Sobolev Norm Learning Rates for Regularized Least-Squares Algorithms JMLR 2020 Minimax Learning of Ergodic Markov Chains ALT 2019 Value-Aware Loss Function for Model-based Reinforcement Learning AISTATS 2017 Finite Sample Prediction and Recovery Bounds for Ordinal Embedding NeurIPS 2016 Alternating Minimization for Regression Problems with Vector-valued Outputs NeurIPS 2015 Learning with Incremental Iterative Regularization NeurIPS 2015