Global optimality of softmax policy gradient with single hidden layer neural networks in the mean-field regime

22 October 2020

Papers citing "Global optimality of softmax policy gradient with single hidden layer neural networks in the mean-field regime"

32 / 32 papers shown

Title
Emergence of meta-stable clustering in mean-field transformer models Giuseppe Bruno Federico Pasqualotto Andrea Agazzi 84 9 0 30 Oct 2024
PC-PG: Policy Cover Directed Exploration for Provable Policy Gradient Learning Alekh Agarwal Mikael Henaff Sham Kakade Wen Sun OffRL 57 109 0 16 Jul 2020
When Do Neural Networks Outperform Kernel Methods? Behrooz Ghorbani Song Mei Theodor Misiakiewicz Andrea Montanari 83 188 0 24 Jun 2020
Can Temporal-Difference and Q-Learning Learn Representation? A Mean-Field Theory Yufeng Zhang Qi Cai Zhuoran Yang Yongxin Chen Zhaoran Wang OOD MLT 269 11 0 08 Jun 2020
On the Convergence of Gradient Descent Training for Two-layer ReLU-networks in the Mean Field Regime Stephan Wojtowytsch MLT 97 50 0 27 May 2020
On the Global Convergence Rates of Softmax Policy Gradient Methods Jincheng Mei Chenjun Xiao Csaba Szepesvári Dale Schuurmans 121 292 0 13 May 2020
Implicit Bias of Gradient Descent for Wide Two-layer Neural Networks Trained with the Logistic Loss Lénaïc Chizat Francis R. Bach MLT 112 338 0 11 Feb 2020
A Rigorous Framework for the Mean Field Limit of Multilayer Neural Networks Phan-Minh Nguyen H. Pham AI4CE 64 81 0 30 Jan 2020
Multi-Agent Reinforcement Learning: A Selective Overview of Theories and Algorithms Kai Zhang Zhuoran Yang Tamer Basar 177 1,213 0 24 Nov 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
Sparse Optimization on Measures with Over-parameterized Gradient Descent Lénaïc Chizat 49 93 0 24 Jul 2019
The Barron Space and the Flow-induced Function Spaces for Neural Network Models E. Weinan Chao Ma Lei Wu 71 110 0 18 Jun 2019
Temporal-difference learning with nonlinear function approximation: lazy training and mean field regimes Andrea Agazzi Jianfeng Lu 31 8 0 27 May 2019
Linearized two-layers neural networks in high dimension Behrooz Ghorbani Song Mei Theodor Misiakiewicz Andrea Montanari MLT 45 243 0 27 Apr 2019
Wide Neural Networks of Any Depth Evolve as Linear Models Under Gradient Descent Jaehoon Lee Lechao Xiao S. Schoenholz Yasaman Bahri Roman Novak Jascha Narain Sohl-Dickstein Jeffrey Pennington 200 1,099 0 18 Feb 2019
Towards moderate overparameterization: global convergence guarantees for training shallow neural networks Samet Oymak Mahdi Soltanolkotabi 48 321 0 12 Feb 2019
Analysis of a Two-Layer Neural Network via Displacement Convexity Adel Javanmard Marco Mondelli Andrea Montanari MLT 78 57 0 05 Jan 2019
Learning to Walk via Deep Reinforcement Learning Tuomas Haarnoja Sehoon Ha Aurick Zhou Jie Tan George Tucker Sergey Levine 100 438 0 26 Dec 2018
On Lazy Training in Differentiable Programming Lénaïc Chizat Edouard Oyallon Francis R. Bach 102 833 0 19 Dec 2018
Stochastic Gradient Descent Optimizes Over-parameterized Deep ReLU Networks Difan Zou Yuan Cao Dongruo Zhou Quanquan Gu ODL 178 448 0 21 Nov 2018
Learning and Generalization in Overparameterized Neural Networks, Going Beyond Two Layers Zeyuan Allen-Zhu Yuanzhi Li Yingyu Liang MLT 183 769 0 12 Nov 2018
A Convergence Theory for Deep Learning via Over-Parameterization Zeyuan Allen-Zhu Yuanzhi Li Zhao Song AI4CE ODL 242 1,462 0 09 Nov 2018
Gradient Descent Finds Global Minima of Deep Neural Networks S. Du Jason D. Lee Haochuan Li Liwei Wang Masayoshi Tomizuka ODL 192 1,134 0 09 Nov 2018
Regularization Matters: Generalization and Optimization of Neural Nets v.s. their Induced Kernel Colin Wei Jason D. Lee Qiang Liu Tengyu Ma 193 244 0 12 Oct 2018
Gradient Descent Provably Optimizes Over-parameterized Neural Networks S. Du Xiyu Zhai Barnabás Póczós Aarti Singh MLT ODL 214 1,270 0 04 Oct 2018
Neural Tangent Kernel: Convergence and Generalization in Neural Networks Arthur Jacot Franck Gabriel Clément Hongler 256 3,194 0 20 Jun 2018
On the Global Convergence of Gradient Descent for Over-parameterized Models using Optimal Transport Lénaïc Chizat Francis R. Bach OT 204 735 0 24 May 2018
A Mean Field View of the Landscape of Two-Layers Neural Networks Song Mei Andrea Montanari Phan-Minh Nguyen MLT 81 858 0 18 Apr 2018
Soft Actor-Critic: Off-Policy Maximum Entropy Deep Reinforcement Learning with a Stochastic Actor Tuomas Haarnoja Aurick Zhou Pieter Abbeel Sergey Levine 290 8,329 0 04 Jan 2018
Bridging the Gap Between Value and Policy Based Reinforcement Learning Ofir Nachum Mohammad Norouzi Kelvin Xu Dale Schuurmans 156 471 0 28 Feb 2017
Playing Atari with Deep Reinforcement Learning Volodymyr Mnih Koray Kavukcuoglu David Silver Alex Graves Ioannis Antonoglou Daan Wierstra Martin Riedmiller 117 12,223 0 19 Dec 2013