Published Online:5 Jan 2024https://doi.org/10.1287/opre.2021.0014
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Volume 72, Issue 5
September-October 2024
Pages iii-vii, 1751-2261, C2-C3
Article Information
Supplemental Material
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Information
- Received:January 08, 2021
- Accepted:December 01, 2022
- Published Online:January 05, 2024
Copyright © 2024 The Author(s)
Cite as
Jalaj Bhandari, Daniel Russo (2024) Global Optimality Guarantees for Policy Gradient Methods. Operations Research 72(5):1906-1927.
https://doi.org/10.1287/opre.2021.0014
Keywords
The authors thank the anonymous referees for feedback that helped improve some aspects of the paper. A part of this work was completed when J. Bhandari was a research fellow at the Theory of Reinforcement learning program at the Simons Institute for the Theory of Computing, University of California, Berkeley. J. Bhandari thanks Peter Bartlett and Simons Institute for that opportunity and Gaurd Iyengar for love and support during the PhD program at Columbia University.
