{"total":23,"rows":[{"id":"2207.04475","title":"Finite-time High-probability Bounds for Polyak-Ruppert Averaged Iterates of Linear Stochastic Approximation","created":"2022-07-10","cited_by_count":41,"area":null},{"id":"2110.14427","title":"The ODE Method for Asymptotic Statistics in Stochastic Approximation and Reinforcement Learning","created":"2021-10-27","cited_by_count":32,"area":null},{"id":"2210.00953","title":"Bias and Extrapolation in Markovian Linear Stochastic Approximation with Constant Stepsizes","created":"2022-10-03","cited_by_count":30,"area":null},{"id":"2303.15740","title":"Concentration of Contractive Stochastic Approximation: Additive and Multiplicative Noise","created":"2023-03-28","cited_by_count":26,"area":null},{"id":"2310.14286","title":"Improved High-Probability Bounds for the Temporal Difference Learning Algorithm via Exponential Stability","created":"2023-10-22","cited_by_count":20,"area":null},{"id":"2405.16644","title":"Gaussian Approximation and Multiplier Bootstrap for Polyak-Ruppert Averaged Linear Stochastic Approximation with Applications to TD Learning","created":"2024-05-26","cited_by_count":19,"area":null},{"id":"2402.04114","title":"SCAFFLSA: Taming Heterogeneity in Federated Linear Stochastic Approximation and TD Learning","created":"2024-02-06","cited_by_count":7,"area":null},{"id":"2303.05838","title":"Rosenthal-type inequalities for linear statistics of Markov chains","created":"2023-03-10","cited_by_count":6,"area":null},{"id":"2304.00707","title":"High-dimensional scaling limits and fluctuations of online least-squares SGD with smooth covariance","created":"2023-04-03","cited_by_count":6,"area":null},{"id":"2410.13067","title":"Two-Timescale Linear Stochastic Approximation: Constant Stepsizes Go a Long Way","created":"2024-10-16","cited_by_count":5,"area":null},{"id":"2505.21796","title":"A General-Purpose Theorem for High-Probability Bounds of Stochastic Approximation with Polyak Averaging","created":"2025-05-27","cited_by_count":4,"area":null},{"id":"2510.12375","title":"Improved Central Limit Theorem and Bootstrap Approximations for Linear Stochastic Approximation","created":"2025-10-14","cited_by_count":4,"area":null},{"id":"2310.18455","title":"Approximate Heavy Tails in Offline (Multi-Pass) Stochastic Gradient Descent","created":"2023-10-27","cited_by_count":3,"area":null},{"id":"2602.02445","title":"Finite-Sample Wasserstein Error Bounds and Concentration Inequalities for Nonlinear Stochastic Approximation","created":"2026-02-02","cited_by_count":3,"area":null},{"id":"2205.12549","title":"Learning from time-dependent streaming data with online stochastic algorithms","created":"2022-05-25","cited_by_count":2,"area":null},{"id":"2509.14039","title":"On the Rate of Gaussian Approximation for Linear Regression Problems","created":"2025-09-17","cited_by_count":2,"area":null},{"id":"2510.12013","title":"Statistical Guarantees for High-Dimensional Stochastic Gradient Descent","created":"2025-10-13","cited_by_count":2,"area":null},{"id":"2302.09727","title":"Statistical Inference for Linear Functionals of Online SGD in High-dimensional Linear Regression","created":"2023-02-20","cited_by_count":1,"area":null},{"id":"2510.19734","title":"Statistical Inference for Linear Functionals of Online Least-squares SGD when $t \\gtrsim d^{1+\\delta}$","created":"2025-10-22","cited_by_count":1,"area":null},{"id":"2605.17678","title":"On Gaussian approximation for entropy-regularized Q-learning with function approximation","created":"2026-05-17","cited_by_count":0,"area":null},{"id":"2607.17595","title":"Concentration and Mean-Square Bounds for Contractive Stochastic Approximation: A Unified Elementary Approach","created":"2026-07-20","cited_by_count":0,"area":null},{"id":"2609.32962","title":"Clipped or Unclipped? Finite-Sample Trade-offs for Averaged SGD under Heavy-Tailed Noise","created":"2026-09-26","cited_by_count":0,"area":null},{"id":"2610.05599","title":"Gaussian Limits for SGD Without Stationary Moments","created":"2026-10-04","cited_by_count":0,"area":null}],"next_cursor":null}