82 citations · 384 across the 49 of their papers we have counts for
6 papers · 1 filter
Learning Good State and Action Representations via Tensor Decomposition
Chengzhuo Ni, Yaqi Duan, Munther Dahleh +2
The transition kernel of a continuous-state-action Markov decision process (MDP) admits a natural tensor structure. This paper proposes a tensor-inspired unsupervised learning meth…
Low-rank Tensor Estimation via Riemannian Gauss-Newton: Statistical Optimality and Second-Order Convergence
Yuetian Luo, Anru R. Zhang
In this paper, we consider the estimation of a low Tucker rank tensor from a number of noisy linear measurements. The general problem covers many specific examples arising from app…
Open Problem: Average-Case Hardness of Hypergraphic Planted Clique Detection
Yuetian Luo, Anru R. Zhang
We note the significance of hypergraphic planted clique (HPC) detection in the investigation of computational hardness for a range of tensor problems. We ask if more evidence for t…
ISLET: Fast and Optimal Low-rank Tensor Regression via Importance Sketching
Anru Zhang, Yuetian Luo, Garvesh Raskutti +1
In this paper, we develop a novel procedure for low-rank tensor regression, namely \emph{\underline{I}mportance \underline{S}ketching \underline{L}ow-rank \underline{E}stimation fo…
Estimation of Markov Chain via Rank-Constrained Likelihood
Xudong Li, Mengdi Wang, Anru Zhang
This paper studies the estimation of low-rank Markov chains from empirical trajectories. We propose a non-convex estimator based on rank-constrained likelihood maximization. Statis…
Spectral State Compression of Markov Processes
Anru Zhang, Mengdi Wang
Model reduction of Markov processes is a basic problem in modeling state-transition systems. Motivated by the state aggregation approach rooted in control theory, we study the stat…