research
∙
09/01/2023
Population-level Balance in Signed Networks
Statistical network models are useful for understanding the underlying f...
share
research
∙
05/15/2023
Fair Information Spread on Social Networks with Community Structure
Information spread through social networks is ubiquitous. Influence maxi...
research
∙
02/22/2023
Incorporating External Risk Information with the Cox Model under Population Heterogeneity: Applications to Trans-Ancestry Polygenic Hazard Scores
Polygenic hazard score (PHS) models designed for European ancestry (EUR)...
research
∙
02/20/2023
Conformal Prediction for Network-Assisted Regression
An important problem in network analysis is predicting a node attribute ...
research
∙
11/18/2022
Wilks' theorems in the β-model
Likelihood ratio tests and the Wilks theorems have been pivotal in stati...
research
∙
10/14/2022
Latent process models for functional network data
Network data are often sampled with auxiliary information or collected t...
research
∙
06/16/2022
Variational Estimators of the Degree-corrected Latent Block Model for Bipartite Networks
Biclustering on bipartite graphs is an unsupervised learning task that s...
research
∙
06/16/2022
Adaptive Algorithm for Quantum Amplitude Estimation
Quantum amplitude estimation is a key sub-routine of a number of quantum...
research
∙
03/12/2022
Distributed Community Detection in Large Networks
Community detection for large networks is a challenging task due to the ...
research
∙
12/28/2020
Latent space models for multiplex networks with shared structure
Latent space models are frequently used for modeling single-layer networ...
research
∙
12/15/2020
Limiting laws and consistent estimation criteria for fixed and diverging number of spiked eigenvalues
In this paper, we study limiting laws and consistent estimation criteria...
research
∙
11/01/2020
Fast Network Community Detection with Profile-Pseudo Likelihood Methods
The stochastic block model is one of the most studied network models for...
research
∙
09/07/2020
Survival Analysis via Ordinary Differential Equations
This paper introduces a general framework for survival analysis based on...
research
∙
08/19/2020
SODEN: A Scalable Continuous-Time Survival Model through Ordinary Differential Equation Networks
In this paper, we propose a flexible model for survival analysis using n...
research
∙
08/09/2020
Community models for partially observed networks from surveys
Communities are a common and widely studied structure in networks, typic...
research
∙
01/29/2020
Network-Assisted Estimation for Large-dimensional Factor Model with Guaranteed Convergence Rate Improvement
Network structure is growing popular for capturing the intrinsic relatio...
research
∙
12/27/2019
Minorization-Maximization-based Steepest Ascent for Large-scale Survival Analysis with Time-Varying Effects: Application to the National Kidney Transplant Dataset
The time-varying effects model is a flexible and powerful tool for model...
research
∙
07/04/2019
High-dimensional Gaussian graphical model for network-linked data
Graphical models are commonly used to represent conditional dependence r...
research
∙
05/26/2019
A Flexible Generative Framework for Graph-based Semi-supervised Learning
We consider a family of problems that are concerned about making predict...
research
∙
02/02/2019
Online Multi-Object Tracking with Dual Matching Attention Networks
In this paper, we propose an online Multi-Object Tracking (MOT) approach...
research
∙
12/02/2018
Model Selection and estimation of Multi Screen Penalty
We propose a multi-step method, called Multi Screen Penalty (MSP), to es...
research
∙
05/17/2018
Covariance-Insured Screening
Modern bio-technologies have produced a vast amount of high-throughput d...
research
∙
03/12/2018
Link prediction for egocentrically sampled networks
Link prediction in networks is typically accomplished by estimating or r...
research
∙
05/18/2017
Generalized linear models with low rank effects for network data
Networks are a useful representation for data on connections between uni...
research
∙
11/04/2016
Classification with Ultrahigh-Dimensional Features
Although much progress has been made in classification with high-dimensi...
research
∙
09/29/2015
Estimating network edge probabilities by neighborhood smoothing
The estimation of probabilities of network edges from the observed adjac...
research
∙
09/03/2015
Community Detection in Networks with Node Features
Many methods have been proposed for community detection in networks, but...
research
∙
12/10/2014
Detecting Overlapping Communities in Networks Using Spectral Methods
Community detection is a fundamental problem in network analysis which i...
research
∙
04/09/2013
High-dimensional Mixed Graphical Models
While graphical models for continuous data (Gaussian graphical models) a...
research
∙
01/29/2013
Link prediction for partially observed networks
Link prediction is one of the fundamental problems in network analysis. ...
research
∙
09/27/2012
Sparse Ising Models with Covariates
There has been a lot of work fitting Ising models to multivariate binary...
research
∙
08/16/2007
