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Learning Markov models via low-rank optimization
v1v2 (latest)

Learning Markov models via low-rank optimization

Operational Research (OR), 2019
28 June 2019
Ziwei Zhu
Xudong Li
Mengdi Wang
Anru R. Zhang
ArXiv (abs)PDFHTML

Papers citing "Learning Markov models via low-rank optimization"

10 / 10 papers shown
Low-Rank Tensors for Multi-Dimensional Markov Models
Low-Rank Tensors for Multi-Dimensional Markov ModelsIEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP), 2024
Madeline Navarro
Sergio Rozada
Antonio G. Marques
Santiago Segarra
302
2
0
04 Nov 2024
Estimating the number of clusters of a Block Markov Chain
Estimating the number of clusters of a Block Markov Chain
T. Vuren
Thomas Cronk
Jaron Sanders
320
3
0
25 Jul 2024
ULTRA-MC: A Unified Approach to Learning Mixtures of Markov Chains via
  Hitting Times
ULTRA-MC: A Unified Approach to Learning Mixtures of Markov Chains via Hitting Times
Fabian Spaeh
Konstantinos Sotiropoulos
Charalampos E. Tsourakakis
324
2
0
23 May 2024
From Self-Attention to Markov Models: Unveiling the Dynamics of
  Generative Transformers
From Self-Attention to Markov Models: Unveiling the Dynamics of Generative Transformers
M. E. Ildiz
Yixiao Huang
Yingcong Li
A. S. Rawat
Samet Oymak
311
43
0
21 Feb 2024
Spectral Entry-wise Matrix Estimation for Low-Rank Reinforcement
  Learning
Spectral Entry-wise Matrix Estimation for Low-Rank Reinforcement LearningNeural Information Processing Systems (NeurIPS), 2023
Stefan Stojanovic
Yassir Jedra
Alexandre Proutière
361
5
0
10 Oct 2023
Singular value distribution of dense random matrices with block
  Markovian dependence
Singular value distribution of dense random matrices with block Markovian dependenceStochastic Processes and their Applications (SPA), 2022
J. Sanders
Alexander Van Werde
383
5
0
28 Apr 2022
Likelihood estimation of sparse topic distributions in topic models and
  its applications to Wasserstein document distance calculations
Likelihood estimation of sparse topic distributions in topic models and its applications to Wasserstein document distance calculations
Xin Bing
F. Bunea
Seth Strimas-Mackey
M. Wegkamp
286
5
0
12 Jul 2021
Learning Good State and Action Representations via Tensor Decomposition
Learning Good State and Action Representations via Tensor DecompositionJournal of machine learning research (JMLR), 2021
Chengzhuo Ni
Yaqi Duan
M. Dahleh
Anru R. Zhang
Mengdi Wang
325
8
0
03 May 2021
Optimal High-order Tensor SVD via Tensor-Train Orthogonal Iteration
Optimal High-order Tensor SVD via Tensor-Train Orthogonal IterationIEEE Transactions on Information Theory (IEEE Trans. Inf. Theory), 2020
Yuchen Zhou
Anru R. Zhang
Lili Zheng
Yazhen Wang
449
26
0
06 Oct 2020
Spectral thresholding for the estimation of Markov chain transition
  operators
Spectral thresholding for the estimation of Markov chain transition operators
Matthias Loffler
A. Picard
511
6
0
24 Aug 2018
1
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