A general sample complexity analysis of vanilla policy gradient

23 July 2021

Papers citing "A general sample complexity analysis of vanilla policy gradient"

44 / 44 papers shown

Title
RobotIQ: Empowering Mobile Robots with Human-Level Planning for Real-World Execution Emmanuel K. Raptis Athanasios Ch. Kapoutsis Elias B. Kosmatopoulos LM&Ro 75 0 0 18 Feb 2025
Small steps no more: Global convergence of stochastic gradient bandits for arbitrary learning rates Jincheng Mei Bo Dai Alekh Agarwal Sharan Vaswani Anant Raj Csaba Szepesvári Dale Schuurmans 84 0 0 11 Feb 2025
A learning-based approach to stochastic optimal control under reach-avoid constraint Tingting Ni Maryam Kamgarpour 70 0 0 21 Dec 2024
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 80 1 0 20 Dec 2024
Structure Matters: Dynamic Policy Gradient Sara Klein Xiangyuan Zhang Tamer Basar Simon Weissmann Leif Döring 35 0 0 07 Nov 2024
On The Global Convergence Of Online RLHF With Neural Parametrization Mudit Gaur Amrit Singh Bedi Raghu Pasupathy Vaneet Aggarwal 21 0 0 21 Oct 2024
Loss Landscape Characterization of Neural Networks without Over-Parametrization Rustem Islamov Niccolò Ajroldi Antonio Orvieto Aurélien Lucchi 33 4 0 16 Oct 2024
Improved Sample Complexity for Global Convergence of Actor-Critic Algorithms Navdeep Kumar Priyank Agrawal Giorgia Ramponi Kfir Y. Levy Shie Mannor 23 0 0 11 Oct 2024
Towards Fast Rates for Federated and Multi-Task Reinforcement Learning Feng Zhu Robert W. Heath Jr. Aritra Mitra 35 1 0 09 Sep 2024
Complexity of Minimizing Projected-Gradient-Dominated Functions with Stochastic First-order Oracles Saeed Masiha Saber Salehkaleybar Niao He Negar Kiyavash Patrick Thiran 27 2 0 03 Aug 2024
Last-Iterate Global Convergence of Policy Gradients for Constrained Reinforcement Learning Alessandro Montenegro Marco Mussi Matteo Papini Alberto Maria Metelli BDL 38 1 0 15 Jul 2024
Almost sure convergence rates of stochastic gradient methods under gradient domination Simon Weissmann Sara Klein Waïss Azizian Leif Döring 26 3 0 22 May 2024
Policy Gradient with Active Importance Sampling Matteo Papini Giorgio Manganini Alberto Maria Metelli Marcello Restelli OffRL 21 1 0 09 May 2024
Learning Optimal Deterministic Policies with Stochastic Policy Gradients Alessandro Montenegro Marco Mussi Alberto Maria Metelli Matteo Papini 38 2 0 03 May 2024
Asynchronous Federated Reinforcement Learning with Policy Gradient Updates: Algorithm Design and Convergence Analysis Guangchen Lan Dong-Jun Han Abolfazl Hashemi Vaneet Aggarwal Christopher G. Brinton 122 15 0 09 Apr 2024
Global Convergence Guarantees for Federated Policy Gradient Methods with Adversaries Swetha Ganesh Jiayu Chen Gugan Thoppe Vaneet Aggarwal FedML 56 1 0 15 Mar 2024
Towards Efficient Risk-Sensitive Policy Gradient: An Iteration Complexity Analysis Rui Liu Erfaun Noorani Pratap Tokekar John S. Baras 23 1 0 13 Mar 2024
Towards Provable Log Density Policy Gradient Pulkit Katdare Anant Joshi Katherine Driggs-Campbell 24 0 0 03 Mar 2024
Stochastic Gradient Succeeds for Bandits Jincheng Mei Zixin Zhong Bo Dai Alekh Agarwal Csaba Szepesvári Dale Schuurmans 19 1 0 27 Feb 2024
On the Complexity of Finite-Sum Smooth Optimization under the Polyak-Łojasiewicz Condition Yunyan Bai Yuxing Liu Luo Luo 13 0 0 04 Feb 2024
On the Stochastic (Variance-Reduced) Proximal Gradient Method for Regularized Expected Reward Optimization Ling Liang Haizhao Yang 14 0 0 23 Jan 2024
Global Convergence of Natural Policy Gradient with Hessian-aided Momentum Variance Reduction Jie Feng Ke Wei Jinchi Chen 20 1 0 02 Jan 2024
A safe exploration approach to constrained Markov decision processes Tingting Ni Maryam Kamgarpour 20 3 0 01 Dec 2023
On the Second-Order Convergence of Biased Policy Gradient Algorithms Siqiao Mu Diego Klabjan 35 2 0 05 Nov 2023
Improved Sample Complexity Analysis of Natural Policy Gradient Algorithm with General Parameterization for Infinite Horizon Discounted Reward Markov Decision Processes Washim Uddin Mondal Vaneet Aggarwal 27 9 0 18 Oct 2023
Beyond Stationarity: Convergence Analysis of Stochastic Softmax Policy Gradient Methods Sara Klein Simon Weissmann Leif Döring 16 7 0 04 Oct 2023
A Homogenization Approach for Gradient-Dominated Stochastic Optimization Jiyuan Tan Chenyu Xue Chuwen Zhang Qi Deng Dongdong Ge Yinyu Ye 23 2 0 21 Aug 2023
Fine-Tuning Language Models with Advantage-Induced Policy Alignment Banghua Zhu Hiteshi Sharma Felipe Vieira Frujeri Shi Dong Chenguang Zhu Michael I. Jordan Jiantao Jiao OSLM 23 39 0 04 Jun 2023
Reinforcement Learning with General Utilities: Simpler Variance Reduction and Large State-Action Space Anas Barakat Ilyas Fatkhullin Niao He 23 11 0 02 Jun 2023
On the Linear Convergence of Policy Gradient under Hadamard Parameterization Jiacai Liu Jinchi Chen Ke Wei 14 2 0 31 May 2023
Decision-Aware Actor-Critic with Function Approximation and Theoretical Guarantees Sharan Vaswani A. Kazemi Reza Babanezhad Nicolas Le Roux OffRL 13 3 0 24 May 2023
Optimal Convergence Rate for Exact Policy Mirror Descent in Discounted Markov Decision Processes Emmeran Johnson Ciara Pike-Burke Patrick Rebeschini 26 11 0 22 Feb 2023
Stochastic Policy Gradient Methods: Improved Sample Complexity for Fisher-non-degenerate Policies Ilyas Fatkhullin Anas Barakat Anastasia Kireeva Niao He 19 37 0 03 Feb 2023
A Novel Framework for Policy Mirror Descent with General Parameterization and Linear Convergence Carlo Alfano Rui Yuan Patrick Rebeschini 54 15 0 30 Jan 2023
Stochastic Dimension-reduced Second-order Methods for Policy Optimization Jinsong Liu Chen Xie Qinwen Deng Dongdong Ge Yi-Li Ye 13 1 0 28 Jan 2023
Understanding the Complexity Gains of Single-Task RL with a Curriculum Qiyang Li Yuexiang Zhai Yi-An Ma Sergey Levine 27 14 0 24 Dec 2022
On the Global Convergence of Fitted Q-Iteration with Two-layer Neural Network Parametrization Mudit Gaur Vaneet Aggarwal Mridul Agarwal MLT 33 1 0 14 Nov 2022
From Gradient Flow on Population Loss to Learning with Stochastic Gradient Descent Satyen Kale Jason D. Lee Chris De Sa Ayush Sekhari Karthik Sridharan 19 4 0 13 Oct 2022
Stochastic Second-Order Methods Improve Best-Known Sample Complexity of SGD for Gradient-Dominated Function Saeed Masiha Saber Salehkaleybar Niao He Negar Kiyavash Patrick Thiran 79 18 0 25 May 2022
Beyond Exact Gradients: Convergence of Stochastic Soft-Max Policy Gradient Methods with Entropy Regularization Yuhao Ding Junzi Zhang Hyunin Lee Javad Lavaei 24 18 0 19 Oct 2021
On the Global Optimum Convergence of Momentum-based Policy Gradient Yuhao Ding Junzi Zhang Javad Lavaei 19 16 0 19 Oct 2021
On the Convergence and Sample Efficiency of Variance-Reduced Policy Gradient Method Junyu Zhang Chengzhuo Ni Zheng Yu Csaba Szepesvári Mengdi Wang 44 66 0 17 Feb 2021
On the Sample Complexity of Actor-Critic Method for Reinforcement Learning with Function Approximation Harshat Kumar Alec Koppel Alejandro Ribeiro 99 79 0 18 Oct 2019
Smoothing Policies and Safe Policy Gradients Matteo Papini Matteo Pirotta Marcello Restelli 11 29 0 08 May 2019