59 citations · 74 across the 16 of their papers we have counts for
16 papers
Improved Naive Bayes with Mislabeled Data
Qianhan Zeng, Yingqiu Zhu, Xuening Zhu +5
Labeling mistakes are frequently encountered in real-world applications. If not treated well, the labeling mistakes can deteriorate the classification performances of a model serio…
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…
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…
CoGANPPIS: A Coevolution-enhanced Global Attention Neural Network for Protein-Protein Interaction Site Prediction
Jiaxing Guo, Xuening Zhu, Zixin Hu +1
Protein-protein interactions are of great importance in biochemical processes. Accurate prediction of protein-protein interaction sites (PPIs) is crucial for our understanding of b…
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.…
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…
Distributed Estimation and Inference for Spatial Autoregression Model with Large Scale Networks
Yimeng Ren, Zhe Li, Xuening Zhu +2
The rapid growth of online network platforms generates large-scale network data and it poses great challenges for statistical analysis using the spatial autoregression (SAR) model.…
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…
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…
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…
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…
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…
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)…
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…
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…
Learning Human Activity Patterns using Clustered Point Processes with Active and Inactive States
Jingfei Zhang, Biao Cai, Xuening Zhu +3
Modeling event patterns is a central task in a wide range of disciplines. In applications such as studying human activity patterns, events often arrive clustered with sporadic and…