Tensor and Matrix Low-Rank Value-Function Approximation in Reinforcement Learning

21 January 2022

Papers citing "Tensor and Matrix Low-Rank Value-Function Approximation in Reinforcement Learning"

10 / 10 papers shown

Title
A Tensor Low-Rank Approximation for Value Functions in Multi-Task Reinforcement Learning Sergio Rozada Santiago Paternain J. Bazerque Antonio G. Marques 62 0 0 17 Jan 2025
Solving Finite-Horizon MDPs via Low-Rank Tensors Sergio Rozada Jose Luis Orejuela Antonio G. Marques 29 0 0 17 Jan 2025
Low-Rank Tensors for Multi-Dimensional Markov Models Madeline Navarro Sergio Rozada Antonio G. Marques Santiago Segarra 28 2 0 04 Nov 2024
Model-free Low-Rank Reinforcement Learning via Leveraged Entry-wise Matrix Estimation Stefan Stojanovic Yassir Jedra Alexandre Proutiere 21 0 0 30 Oct 2024
Tensor Low-rank Approximation of Finite-horizon Value Functions Sergio Rozada Antonio G. Marques 23 3 0 27 May 2024
Matrix Low-Rank Approximation For Policy Gradient Methods Sergio Rozada A. Marques 18 2 0 27 May 2024
Matrix Low-Rank Trust Region Policy Optimization Sergio Rozada Antonio G. Marques 36 0 0 27 May 2024
Overcoming the Long Horizon Barrier for Sample-Efficient Reinforcement Learning with Latent Low-Rank Structure Tyler Sam Yudong Chen C. Yu OffRL 16 6 0 07 Jun 2022
Tensor Decomposition for Signal Processing and Machine Learning N. Sidiropoulos L. De Lathauwer Xiao Fu Kejun Huang Evangelos E. Papalexakis Christos Faloutsos 92 1,342 0 06 Jul 2016
Value function approximation via low-rank models H. Ong OffRL 22 20 0 31 Aug 2015