This paper studies the computational and statistical aspects of quantile...
We investigate a generalized framework for estimating latent low-rank te...
High-dimensional linear regression under heavy-tailed noise or outlier
c...
This paper develops an R package rMultiNet to analyze multilayer network...
Network analysis has been a powerful tool to unveil relationships and
in...
This paper introduces a dual-based algorithm framework for solving the
r...
This paper investigates the computational and statistical limits in
clus...
Low-rank matrix estimation under heavy-tailed noise is challenging, both...
Structural matrix-variate observations routinely arise in diverse fields...
The tensor train (TT) format enjoys appealing advantages in handling
str...
We investigate a generalized framework to estimate a latent low-rank plu...
In this paper, we consider the statistical inference for several low-ran...
This paper introduces a general framework of Semiparametric TEnsor FActo...
We study the problem of community detection in multi-layer networks, whe...
To date, social network analysis has been largely focused on pairwise
in...
We introduce a flexible framework for making inferences about general li...
Matrix singular value decomposition (SVD) is popular in statistical data...
This note displays an interesting phenomenon for percentiles of independ...
Let M∈R^m_1× m_2 be an unknown matrix with r=
rank( M)≪(m_1,m_2) whose ...
Let M∈R^m_1× m_2 be an unknown matrix with r=
rank( M)≪(m_1,m_2) whose ...
In this article, we develop methods for estimating a low rank tensor fro...
In this paper, we investigate effective sketching schemes via sparsifica...
The higher order singular value decomposition (HOSVD) of tensors is a
ge...
In this paper, we propose a general framework for tensor singular value
...
In this paper, we investigate the sample size requirement for exact reco...
Density matrices are positively semi-definite Hermitian matrices with un...
Let S_m be the set of all m× m density matrices
(Hermitian positively s...
Recent studies in the literature have paid much attention to the sparsit...
In this paper, we consider low rank matrix estimation using either
matri...