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20182023
most citedLeast Squares Approximation for a Distributed System

59 citations · 74 across the 16 of their papers we have counts for

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12 papers · 1 filter

stat.ME2023

Subsampling and Jackknifing: A Practically Convenient Solution for Large Data Analysis with Limited Computational Resources

Shuyuan Wu, Xuening Zhu, Hansheng Wang

Modern statistical analysis often encounters datasets with large sizes. For these datasets, conventional estimation methods can hardly be used immediately because practitioners oft…

stat.ME2023★ 2 cited

Distributed Logistic Regression for Massive Data with Rare Events

Xuetong Li, Xuening Zhu, Hansheng Wang

Large-scale rare events data are commonly encountered in practice. To tackle the massive rare events data, we propose a novel distributed estimation method for logistic regression…

stat.ME2023

Network Autoregression for Incomplete Matrix-Valued Time Series

Xuening Zhu, Feifei Wang, Zeng Li +1

We study the dynamics of matrix-valued time series with observed network structures by proposing a matrix network autoregression model with row and column networks of the subjects.…

stat.ME2022★ 1 cited

Matrix-valued Network Autoregression Model with Latent Group Structure

Yimeng Ren, Xuening Zhu, Ganggang Xu +1

Matrix-valued time series data are frequently observed in a broad range of areas and have attracted great attention recently. In this work, we model network effects for high dimens…

stat.ME2022★ 2 cited

Simultaneous Estimation and Group Identification for Network Vector Autoregressive Model with Heterogeneous Nodes

Xuening Zhu, Ganggang Xu, Jianqing Fan

Individuals or companies in a large social or financial network often display rather heterogeneous behaviors for various reasons. In this work, we propose a network vector autoregr…

stat.ME2021★ 3 cited

An Asymptotic Analysis of Minibatch-Based Momentum Methods for Linear Regression Models

Yuan Gao, Xuening Zhu, Haobo Qi +3

Momentum methods have been shown to accelerate the convergence of the standard gradient descent algorithm in practice and theory. In particular, the minibatch-based gradient descen…

stat.ME2021

Graphical Assistant Grouped Network Autoregression Model: a Bayesian Nonparametric Recourse

Yimeng Ren, Xuening Zhu, Guanyu Hu

Vector autoregression model is ubiquitous in classical time series data analysis. With the rapid advance of social network sites, time series data over latent graph is becoming inc…

stat.ME2021★ 1 cited

A Sequential Addressing Subsampling Method for Massive Data Analysis under Memory Constraint

Rui Pan, Yingqiu Zhu, Baishan Guo +2

The emergence of massive data in recent years brings challenges to automatic statistical inference. This is particularly true if the data are too numerous to be read into memory as…

stat.ME2020★ 2 cited

Distributed Community Detection for Large Scale Networks Using Stochastic Block Model

Shihao Wu, Zhe Li, Xuening Zhu

With rapid developments of information and technology, large scale network data are ubiquitous. In this work we develop a distributed spectral clustering algorithm for community de…

stat.ME2020★ 3 cited

Community Network Auto-Regression for High-Dimensional Time Series

Elynn Y. Chen, Jianqing Fan, Xuening Zhu

Modeling responses on the nodes of a large-scale network is an important task that arises commonly in practice. This paper proposes a community network vector autoregressive (CNAR)…

stat.ME2020

Group Network Hawkes Process

Guanhua Fang, Ganggang Xu, Haochen Xu +2

In this work, we study the event occurrences of individuals interacting in a network. To characterize the dynamic interactions among the individuals, we propose a group network Haw…

stat.ME2019★ 59 cited

Least Squares Approximation for a Distributed System

Xuening Zhu, Feng Li, Hansheng Wang

In this work, we develop a distributed least squares approximation (DLSA) method that is able to solve a large family of regression problems (e.g., linear regression, logistic regr…