research
∙
09/06/2023
Quantile and pseudo-Huber Tensor Decomposition
This paper studies the computational and statistical aspects of quantile...
share
research
∙
06/06/2023
Online Tensor Learning: Computational and Statistical Trade-offs, Adaptivity and Optimal Regret
We investigate a generalized framework for estimating latent low-rank te...
research
∙
05/10/2023
Computationally Efficient and Statistically Optimal Robust High-Dimensional Linear Regression
High-dimensional linear regression under heavy-tailed noise or outlier c...
research
∙
02/09/2023
rMultiNet: An R Package For Multilayer Networks Analysis
This paper develops an R package rMultiNet to analyze multilayer network...
research
∙
09/28/2022
Consensus Knowledge Graph Learning via Multi-view Sparse Low Rank Block Model
Network analysis has been a powerful tool to unveil relationships and in...
research
∙
09/01/2022
Optimal Regularized Online Convex Allocation by Adaptive Re-Solving
This paper introduces a dual-based algorithm framework for solving the r...
research
∙
07/11/2022
Optimal Clustering by Lloyd Algorithm for Low-Rank Mixture Model
This paper investigates the computational and statistical limits in clus...
research
∙
03/02/2022
Computationally Efficient and Statistically Optimal Robust Low-rank Matrix and Tensor Estimation
Low-rank matrix estimation under heavy-tailed noise is challenging, both...
research
∙
01/22/2022
Optimal Estimation and Computational Limit of Low-rank Gaussian Mixtures
Structural matrix-variate observations routinely arise in diverse fields...
research
∙
08/27/2021
Provable Tensor-Train Format Tensor Completion by Riemannian Optimization
The tensor train (TT) format enjoys appealing advantages in handling str...
research
∙
03/16/2021
Generalized Low-rank plus Sparse Tensor Estimation by Fast Riemannian Optimization
We investigate a generalized framework to estimate a latent low-rank plu...
research
∙
12/29/2020
Inference for Low-rank Tensors – No Need to Debias
In this paper, we consider the statistical inference for several low-ran...
research
∙
07/05/2020
Semiparametric Tensor Factor Analysis by Iteratively Projected SVD
This paper introduces a general framework of Semiparametric TEnsor FActo...
research
∙
02/10/2020
Community Detection on Mixture Multi-layer Networks via Regularized Tensor Decomposition
We study the problem of community detection in multi-layer networks, whe...
research
∙
09/14/2019
Community Detection for Hypergraph Networks via Regularized Tensor Power Iteration
To date, social network analysis has been largely focused on pairwise in...
research
∙
08/31/2019
Statistical Inferences of Linear Forms for Noisy Matrix Completion
We introduce a flexible framework for making inferences about general li...
research
∙
01/02/2019
Data-dependent Confidence Regions of Singular Subspaces
Matrix singular value decomposition (SVD) is popular in statistical data...
research
∙
08/24/2018
Non-asymptotic bounds for percentiles of independent non-identical random variables
This note displays an interesting phenomenon for percentiles of independ...
research
∙
05/24/2018
Confidence region of singular vectors for high-dimensional and low-rank matrix regression
Let M∈R^m_1× m_2 be an unknown matrix with r= rank( M)≪(m_1,m_2) whose ...
research
∙
05/24/2018
Confidence interval of singular vectors for high-dimensional and low-rank matrix regression
Let M∈R^m_1× m_2 be an unknown matrix with r= rank( M)≪(m_1,m_2) whose ...
research
∙
11/14/2017
Statistically Optimal and Computationally Efficient Low Rank Tensor Completion from Noisy Entries
In this article, we develop methods for estimating a low rank tensor fro...
research
∙
10/31/2017
Effective Tensor Sketching via Sparsification
In this paper, we investigate effective sketching schemes via sparsifica...
research
∙
07/05/2017
The ℓ_∞ Perturbation of HOSVD and Low Rank Tensor Denoising
The higher order singular value decomposition (HOSVD) of tensors is a ge...
research
∙
03/08/2017
Tensor SVD: Statistical and Computational Limits
In this paper, we propose a general framework for tensor singular value ...
research
∙
02/22/2017
On Polynomial Time Methods for Exact Low Rank Tensor Completion
In this paper, we investigate the sample size requirement for exact reco...
research
∙
10/16/2016
Estimation of low rank density matrices by Pauli measurements
Density matrices are positively semi-definite Hermitian matrices with un...
research
∙
04/15/2016
Estimation of low rank density matrices: bounds in Schatten norms and other distances
Let S_m be the set of all m× m density matrices (Hermitian positively s...
research
∙
12/26/2014
Exploring Sparsity in Multi-class Linear Discriminant Analysis
Recent studies in the literature have paid much attention to the sparsit...
research
∙
03/25/2014
