Bias and Extrapolation in Markovian Linear Stochastic Approximation with Constant Stepsizes-Reference-Cited by-同舟云学术

Bias and Extrapolation in Markovian Linear Stochastic Approximation with Constant Stepsizes

Published:2023-06-19 Issue: Volume: Page:
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Container-title:Abstract Proceedings of the 2023 ACM SIGMETRICS International Conference on Measurement and Modeling of Computer Systems
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Author:

Huo Dongyan (Lucy)¹^ORCID,Chen Yudong²^ORCID,Xie Qiaomin²^ORCID

Affiliation:

1. Cornell University, Ithaca, NY, USA

2. University of Wisconsin-Madison, Madison, WI, USA

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3578338.3593526

Reference6 articles.

1. Jalaj Bhandari , Daniel Russo , and Raghav Singal . 2021 . A Finite Time Analysis of Temporal Difference Learning with Linear Function Approximation . Operations Research , Vol. 69 , 3 (01 May 2021), 950--973. https://doi.org/10.1287/opre.2020.2024 10.1287/opre.2020.2024 Jalaj Bhandari, Daniel Russo, and Raghav Singal. 2021. A Finite Time Analysis of Temporal Difference Learning with Linear Function Approximation. Operations Research, Vol. 69, 3 (01 May 2021), 950--973. https://doi.org/10.1287/opre.2020.2024

2. Dongyann (Lucy) Huo Yudong Chen and Qiaomin Xie. 2022. Bias and Extrapolation in Markovian Linear Stochastic Approximation with Constant Stepsizes. https://doi.org/10.48550/ARXIV.2210.00953 10.48550/ARXIV.2210.00953

3. Dongyann (Lucy) Huo Yudong Chen and Qiaomin Xie. 2022. Bias and Extrapolation in Markovian Linear Stochastic Approximation with Constant Stepsizes. https://doi.org/10.48550/ARXIV.2210.00953

4. Chandrashekar Lakshminarayanan and Csaba Szepesvári . 2018 . Linear Stochastic Approximation: How Far Does Constant Step-Size and Iterate Averaging Go? . In Proceedings of the Twenty-First International Conference on Artificial Intelligence and Statistics. PMLR, 1347--1355 . Chandrashekar Lakshminarayanan and Csaba Szepesvári. 2018. Linear Stochastic Approximation: How Far Does Constant Step-Size and Iterate Averaging Go?. In Proceedings of the Twenty-First International Conference on Artificial Intelligence and Statistics. PMLR, 1347--1355.

5. Wenlong Mou , Chris Junchi Li , Martin J. Wainwright , Peter L. Bartlett , and Michael I. Jordan . 2020. On Linear Stochastic Approximation: Fine-grained Polyak-Ruppert and Non-Asymptotic Concentration . In Proceedings of Thirty Third Conference on Learning Theory. PMLR, 2947--2997 . Wenlong Mou, Chris Junchi Li, Martin J. Wainwright, Peter L. Bartlett, and Michael I. Jordan. 2020. On Linear Stochastic Approximation: Fine-grained Polyak-Ruppert and Non-Asymptotic Concentration. In Proceedings of Thirty Third Conference on Learning Theory. PMLR, 2947--2997.

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