polyak-ruppert averaging

A Single Stepsize Suffices for Unprojected Linear TD(0): Simultaneous Robust and Fast Rates via Polyak–Ruppert Averaging COLT 2026 Gaussian Approximation for Two-Timescale Linear Stochastic Approximation AAAI 2026 High-Order Error Bounds for Markovian LSA with Richardson–Romberg Extrapolation AAAI 2026 Parameter-free Optimal Rates for Nonlinear Semi-Norm Contractions with Applications to Q-Learning AAAI 2026 Convergence Rate in a Nonlinear Two-Time-Scale Stochastic Approximation with State (Time)-Dependence AAAI 2025 Computing the Bias of Constant-step Stochastic Approximation with Markovian Noise NeurIPS 2024 Gaussian Approximation and Multiplier Bootstrap for Polyak-Ruppert Averaged Linear Stochastic Approximation with Applications to TD Learning NeurIPS 2024 Improved High-Probability Bounds for the Temporal Difference Learning Algorithm via Exponential Stability COLT 2024 A Statistical Analysis of Polyak-Ruppert Averaged Q-Learning AISTATS 2023 Recursive Quantile Estimation: Non-Asymptotic Confidence Bounds JMLR 2023 Fast and Robust Online Inference with Stochastic Gradient Descent via Random Scaling AAAI 2022 Convergence Rates of Stochastic Gradient Descent under Infinite Noise Variance NeurIPS 2021 On Linear Stochastic Approximation: Fine-grained Polyak-Ruppert and Non-Asymptotic Concentration COLT 2020 Normal Approximation for Stochastic Gradient Descent via Non-Asymptotic Rates of Martingale CLT COLT 2019 Non-Asymptotic Analysis of Stochastic Approximation Algorithms for Machine Learning NeurIPS 2011