Global Optimality Guarantees For Policy Gradient Methods

5 June 2019

Papers citing "Global Optimality Guarantees For Policy Gradient Methods"

50 / 59 papers shown

Title
Near-Optimal Sample Complexity for Iterated CVaR Reinforcement Learning with a Generative Model Zilong Deng Simon Khan Shaofeng Zou 116 0 0 11 Mar 2025
FedRLHF: A Convergence-Guaranteed Federated Framework for Privacy-Preserving and Personalized RLHF Flint Xiaofeng Fan Cheston Tan Yew-Soon Ong Roger Wattenhofer Wei Tsang Ooi 118 1 0 20 Dec 2024
RL-STaR: Theoretical Analysis of Reinforcement Learning Frameworks for Self-Taught Reasoner Fu-Chieh Chang Yu-Ting Lee Hui-Ying Shih Pei-Yuan Wu Pei-Yuan Wu OffRL LRM 378 0 0 31 Oct 2024
Regressing the Relative Future: Efficient Policy Optimization for Multi-turn RLHF Zhaolin Gao Wenhao Zhan Jonathan D. Chang Gokul Swamy Kianté Brantley Jason D. Lee Wen Sun OffRL 119 7 0 06 Oct 2024
Near-Optimal Policy Identification in Robust Constrained Markov Decision Processes via Epigraph Form Toshinori Kitamura Tadashi Kozuno Wataru Kumagai Kenta Hoshino Y. Hosoe Kazumi Kasaura Masashi Hamaya Paavo Parmas Yutaka Matsuo 89 2 0 29 Aug 2024
Functional Acceleration for Policy Mirror Descent Veronica Chelu Doina Precup 62 0 0 23 Jul 2024
Policy Gradient Methods for Risk-Sensitive Distributional Reinforcement Learning with Provable Convergence Minheng Xiao Xian Yu Lei Ying 74 2 0 23 May 2024
Behind the Myth of Exploration in Policy Gradients Adrien Bolland Gaspard Lambrechts Damien Ernst 79 0 0 31 Jan 2024
On the Global Convergence of Risk-Averse Policy Gradient Methods with Expected Conditional Risk Measures Xian Yu Lei Ying 52 5 0 26 Jan 2023
Finite Sample Analysis of Minimax Offline Reinforcement Learning: Completeness, Fast Rates and First-Order Efficiency Masatoshi Uehara Masaaki Imaizumi Nan Jiang Nathan Kallus Wen Sun Tengyang Xie OffRL 41 53 0 05 Feb 2021
What are the Statistical Limits of Offline RL with Linear Function Approximation? Ruosong Wang Dean Phillips Foster Sham Kakade OffRL 149 163 0 22 Oct 2020
Exponential Lower Bounds for Planning in MDPs With Linearly-Realizable Optimal Action-Value Functions Gellert Weisz Philip Amortila Csaba Szepesvári OffRL 147 80 0 03 Oct 2020
Doubly Robust Off-Policy Value and Gradient Estimation for Deterministic Policies Nathan Kallus Masatoshi Uehara OffRL 37 15 0 06 Jun 2020
The Ingredients of Real-World Robotic Reinforcement Learning Henry Zhu Justin Yu Abhishek Gupta Dhruv Shah Kristian Hartikainen Avi Singh Vikash Kumar Sergey Levine OffRL 100 176 0 27 Apr 2020
Statistically Efficient Off-Policy Policy Gradients Nathan Kallus Masatoshi Uehara OffRL 64 39 0 10 Feb 2020
Is a Good Representation Sufficient for Sample Efficient Reinforcement Learning? S. Du Sham Kakade Ruosong Wang Lin F. Yang 173 193 0 07 Oct 2019
Adaptive Trust Region Policy Optimization: Global Convergence and Faster Rates for Regularized MDPs Lior Shani Yonathan Efroni Shie Mannor 49 175 0 06 Sep 2019
Neural Policy Gradient Methods: Global Optimality and Rates of Convergence Lingxiao Wang Qi Cai Zhuoran Yang Zhaoran Wang 77 241 0 29 Aug 2019
On the Theory of Policy Gradient Methods: Optimality, Approximation, and Distribution Shift Alekh Agarwal Sham Kakade Jason D. Lee G. Mahajan 61 320 0 01 Aug 2019
Provably Efficient Reinforcement Learning with Linear Function Approximation Chi Jin Zhuoran Yang Zhaoran Wang Michael I. Jordan 86 556 0 11 Jul 2019
Monte Carlo Gradient Estimation in Machine Learning S. Mohamed Mihaela Rosca Michael Figurnov A. Mnih 67 408 0 25 Jun 2019
Information-Theoretic Considerations in Batch Reinforcement Learning Jinglin Chen Nan Jiang OOD OffRL 147 376 0 01 May 2019
A Theory of Regularized Markov Decision Processes Matthieu Geist B. Scherrer Olivier Pietquin 109 325 0 31 Jan 2019
Soft Actor-Critic Algorithms and Applications Tuomas Haarnoja Aurick Zhou Kristian Hartikainen George Tucker Sehoon Ha ... Vikash Kumar Henry Zhu Abhishek Gupta Pieter Abbeel Sergey Levine 133 2,422 0 13 Dec 2018
Neural Tangent Kernel: Convergence and Generalization in Neural Networks Arthur Jacot Franck Gabriel Clément Hongler 252 3,194 0 20 Jun 2018
Variational Inverse Control with Events: A General Framework for Data-Driven Reward Definition Justin Fu Avi Singh Dibya Ghosh Larry Yang Sergey Levine BDL 41 125 0 29 May 2018
Stochastic subgradient method converges on tame functions Damek Davis Dmitriy Drusvyatskiy Sham Kakade Jason D. Lee 56 251 0 20 Apr 2018
Feature-Based Aggregation and Deep Reinforcement Learning: A Survey and Some New Implementations Dimitri Bertsekas OffRL 53 131 0 12 Apr 2018
On the Power of Over-parametrization in Neural Networks with Quadratic Activation S. Du Jason D. Lee 160 271 0 03 Mar 2018
Global Convergence of Policy Gradient Methods for the Linear Quadratic Regulator Maryam Fazel Rong Ge Sham Kakade M. Mesbahi 77 601 0 15 Jan 2018
Proximal Policy Optimization Algorithms John Schulman Filip Wolski Prafulla Dhariwal Alec Radford Oleg Klimov OffRL 446 18,931 0 20 Jul 2017
Proximally Guided Stochastic Subgradient Method for Nonsmooth, Nonconvex Problems Damek Davis Benjamin Grimmer 48 113 0 12 Jul 2017
Parameter Space Noise for Exploration Matthias Plappert Rein Houthooft Prafulla Dhariwal Szymon Sidor Richard Y. Chen Xi Chen Tamim Asfour Pieter Abbeel Marcin Andrychowicz 52 595 0 06 Jun 2017
Deep Exploration via Randomized Value Functions Ian Osband Benjamin Van Roy Daniel Russo Zheng Wen 89 306 0 22 Mar 2017
Evolution Strategies as a Scalable Alternative to Reinforcement Learning Tim Salimans Jonathan Ho Xi Chen Szymon Sidor Ilya Sutskever 92 1,537 0 10 Mar 2017
Towards Generalization and Simplicity in Continuous Control Aravind Rajeswaran Kendall Lowrey E. Todorov Sham Kakade OffRL 86 276 0 08 Mar 2017
How to Escape Saddle Points Efficiently Chi Jin Rong Ge Praneeth Netrapalli Sham Kakade Michael I. Jordan ODL 213 836 0 02 Mar 2017
Improving Policy Gradient by Exploring Under-appreciated Rewards Ofir Nachum Mohammad Norouzi Dale Schuurmans 66 44 0 28 Nov 2016
Linear Convergence of Gradient and Proximal-Gradient Methods Under the Polyak-Łojasiewicz Condition Hamed Karimi J. Nutini Mark Schmidt 262 1,218 0 16 Aug 2016
Stochastic Frank-Wolfe Methods for Nonconvex Optimization Sashank J. Reddi S. Sra Barnabás Póczós Alex Smola 57 140 0 27 Jul 2016
Matrix Completion has No Spurious Local Minimum Rong Ge Jason D. Lee Tengyu Ma 99 599 0 24 May 2016
Global Optimality of Local Search for Low Rank Matrix Recovery Srinadh Bhojanapalli Behnam Neyshabur Nathan Srebro ODL 100 388 0 23 May 2016
Deep Learning without Poor Local Minima Kenji Kawaguchi ODL 213 922 0 23 May 2016
Stochastic Variance Reduction for Nonconvex Optimization Sashank J. Reddi Ahmed S. Hefny S. Sra Barnabás Póczós Alex Smola 92 600 0 19 Mar 2016
Asynchronous Methods for Deep Reinforcement Learning Volodymyr Mnih Adria Puigdomenech Badia M. Berk Mirza Alex Graves Timothy Lillicrap Tim Harley David Silver Koray Kavukcuoglu 191 8,833 0 04 Feb 2016
Complete Dictionary Recovery over the Sphere I: Overview and the Geometric Picture Ju Sun Qing Qu John N. Wright 114 159 0 11 Nov 2015
High-Dimensional Continuous Control Using Generalized Advantage Estimation John Schulman Philipp Moritz Sergey Levine Michael I. Jordan Pieter Abbeel OffRL 84 3,399 0 08 Jun 2015
Escaping From Saddle Points --- Online Stochastic Gradient for Tensor Decomposition Rong Ge Furong Huang Chi Jin Yang Yuan 135 1,058 0 06 Mar 2015
Trust Region Policy Optimization John Schulman Sergey Levine Philipp Moritz Michael I. Jordan Pieter Abbeel 277 6,764 0 19 Feb 2015
On the Computational Efficiency of Training Neural Networks Roi Livni Shai Shalev-Shwartz Ohad Shamir 139 479 0 05 Oct 2014