1.6k citations · 4.2k across the 71 of their papers we have counts for
7 papers · 1 filter
Mixing time estimation in reversible Markov chains from a single sample path
Daniel Hsu, Aryeh Kontorovich, David A. Levin +2
The spectral gap of a finite, ergodic, and reversible Markov chain is an important parameter measuring the asymptotic rate of convergence. In applications, the transition matri…
Parameter identification in Markov chain choice models
Arushi Gupta, Daniel Hsu
This work studies the parameter identification problem for the Markov chain choice model of Blanchet, Gallego, and Goyal used in assortment planning. In this model, the product sel…
Coding sets with asymmetric information
Alexandr Andoni, Javad Ghaderi, Daniel Hsu +2
We study the following one-way asymmetric transmission problem, also a variant of model-based compressed sensing: a resource-limited encoder has to report a small set from a un…
Greedy Approaches to Symmetric Orthogonal Tensor Decomposition
Cun Mu, Daniel Hsu, Donald Goldfarb
Finding the symmetric and orthogonal decomposition (SOD) of a tensor is a recurring problem in signal processing, machine learning and statistics. In this paper, we review, establi…
Successive Rank-One Approximations for Nearly Orthogonally Decomposable Symmetric Tensors
Cun Mu, Daniel Hsu, Donald Goldfarb
Many idealized problems in signal processing, machine learning and statistics can be reduced to the problem of finding the symmetric canonical decomposition of an underlying symmet…
Linear regression without correspondence
Daniel Hsu, Kevin Shi, Xiaorui Sun
This article considers algorithmic and statistical aspects of linear regression when the correspondence between the covariates and the responses is unknown. First, a fully polynomi…