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Temporal-difference learning with nonlinear function approximation: lazy
  training and mean field regimes

Temporal-difference learning with nonlinear function approximation: lazy training and mean field regimes

27 May 2019
Andrea Agazzi
Jianfeng Lu
ArXivPDFHTML

Papers citing "Temporal-difference learning with nonlinear function approximation: lazy training and mean field regimes"

6 / 6 papers shown
Title
The RL Perceptron: Generalisation Dynamics of Policy Learning in High
  Dimensions
The RL Perceptron: Generalisation Dynamics of Policy Learning in High Dimensions
Nishil Patel
Sebastian Lee
Stefano Sarao Mannelli
Sebastian Goldt
Adrew Saxe
OffRL
28
3
0
17 Jun 2023
Towards a Better Understanding of Representation Dynamics under
  TD-learning
Towards a Better Understanding of Representation Dynamics under TD-learning
Yunhao Tang
Rémi Munos
OffRL
26
1
0
29 May 2023
Global Optimality of Elman-type RNN in the Mean-Field Regime
Global Optimality of Elman-type RNN in the Mean-Field Regime
Andrea Agazzi
Jian-Xiong Lu
Sayan Mukherjee
MLT
34
1
0
12 Mar 2023
Gauss-Newton Temporal Difference Learning with Nonlinear Function
  Approximation
Gauss-Newton Temporal Difference Learning with Nonlinear Function Approximation
Zhifa Ke
Junyu Zhang
Zaiwen Wen
24
0
0
25 Feb 2023
Global optimality of softmax policy gradient with single hidden layer
  neural networks in the mean-field regime
Global optimality of softmax policy gradient with single hidden layer neural networks in the mean-field regime
Andrea Agazzi
Jianfeng Lu
13
15
0
22 Oct 2020
Can Temporal-Difference and Q-Learning Learn Representation? A
  Mean-Field Theory
Can Temporal-Difference and Q-Learning Learn Representation? A Mean-Field Theory
Yufeng Zhang
Qi Cai
Zhuoran Yang
Yongxin Chen
Zhaoran Wang
OOD
MLT
90
11
0
08 Jun 2020
1