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Adaptive Low-Nonnegative-Rank Approximation for State Aggregation of
  Markov Chains

Adaptive Low-Nonnegative-Rank Approximation for State Aggregation of Markov Chains

14 October 2018
Yaqi Duan
Mengdi Wang
Zaiwen Wen
Ya-Xiang Yuan
ArXiv (abs)PDFHTML

Papers citing "Adaptive Low-Nonnegative-Rank Approximation for State Aggregation of Markov Chains"

4 / 4 papers shown
Title
Optimal High-order Tensor SVD via Tensor-Train Orthogonal Iteration
Optimal High-order Tensor SVD via Tensor-Train Orthogonal Iteration
Yuchen Zhou
Anru R. Zhang
Lili Zheng
Yazhen Wang
105
22
0
06 Oct 2020
FLAMBE: Structural Complexity and Representation Learning of Low Rank
  MDPs
FLAMBE: Structural Complexity and Representation Learning of Low Rank MDPs
Alekh Agarwal
Sham Kakade
A. Krishnamurthy
Wen Sun
OffRL
197
227
0
18 Jun 2020
Can Agents Learn by Analogy? An Inferable Model for PAC Reinforcement
  Learning
Can Agents Learn by Analogy? An Inferable Model for PAC Reinforcement Learning
Yanchao Sun
Furong Huang
63
4
0
21 Dec 2019
Spectral thresholding for the estimation of Markov chain transition
  operators
Spectral thresholding for the estimation of Markov chain transition operators
Matthias Loffler
A. Picard
74
6
0
24 Aug 2018
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