Dong Xia | DeepAI

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∙ 02/09/2023

rMultiNet: An R Package For Multilayer Networks Analysis

This paper develops an R package rMultiNet to analyze multilayer network...

0 Ting Li, et al. ∙

∙ 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...

0 Tianxi Cai, et al. ∙

∙ 09/01/2022

Optimal Regularized Online Convex Allocation by Adaptive Re-Solving

This paper introduces a dual-based algorithm framework for solving the r...

0 Wanteng Ma, et al. ∙

∙ 07/11/2022

Optimal Clustering by Lloyd Algorithm for Low-Rank Mixture Model

This paper investigates the computational and statistical limits in clus...

0 Zhongyuan Lyu, et al. ∙

∙ 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...

0 Yinan Shen, et al. ∙

∙ 01/22/2022

Optimal Estimation and Computational Limit of Low-rank Gaussian Mixtures

Structural matrix-variate observations routinely arise in diverse fields...

0 Zhongyuan Lyu, et al. ∙

∙ 08/27/2021

Provable Tensor-Train Format Tensor Completion by Riemannian Optimization

The tensor train (TT) format enjoys appealing advantages in handling str...

0 Jian-Feng Cai, et al. ∙

∙ 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...

0 Jian-Feng Cai, et al. ∙

∙ 12/29/2020

Inference for Low-rank Tensors – No Need to Debias

In this paper, we consider the statistical inference for several low-ran...

0 Dong Xia, et al. ∙

∙ 07/05/2020

Semiparametric Tensor Factor Analysis by Iteratively Projected SVD

This paper introduces a general framework of Semiparametric TEnsor FActo...

0 Elynn Y. Chen, et al. ∙

∙ 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...

0 Bing-Yi Jing, et al. ∙

∙ 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...

0 Zheng Tracy Ke, et al. ∙

∙ 08/31/2019

Statistical Inferences of Linear Forms for Noisy Matrix Completion

We introduce a flexible framework for making inferences about general li...

0 Dong Xia, et al. ∙

∙ 01/02/2019

Data-dependent Confidence Regions of Singular Subspaces

Matrix singular value decomposition (SVD) is popular in statistical data...

0 Dong Xia, et al. ∙

∙ 08/24/2018

Non-asymptotic bounds for percentiles of independent non-identical random variables

This note displays an interesting phenomenon for percentiles of independ...

0 Dong Xia, et al. ∙

∙ 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 ...

0 Dong Xia, et al. ∙

∙ 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 ...

0 Dong Xia, et al. ∙

∙ 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...

0 Dong Xia, et al. ∙

∙ 10/31/2017

Effective Tensor Sketching via Sparsification

In this paper, we investigate effective sketching schemes via sparsifica...

0 Dong Xia, et al. ∙

∙ 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...

0 Dong Xia, et al. ∙

∙ 03/08/2017

Tensor SVD: Statistical and Computational Limits

In this paper, we propose a general framework for tensor singular value ...

0 Anru Zhang, et al. ∙

∙ 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...

0 Dong Xia, et al. ∙

∙ 10/16/2016

Estimation of low rank density matrices by Pauli measurements

Density matrices are positively semi-definite Hermitian matrices with un...

0 Dong Xia, et al. ∙

∙ 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...

0 Dong Xia, et al. ∙

∙ 12/26/2014

Exploring Sparsity in Multi-class Linear Discriminant Analysis

Recent studies in the literature have paid much attention to the sparsit...

0 Dong Xia, et al. ∙

∙ 03/25/2014

Optimal Schatten-q and Ky-Fan-k Norm Rate of Low Rank Matrix Estimation

In this paper, we consider low rank matrix estimation using either matri...

0 Dong Xia, et al. ∙