
Latent space models for multiplex networks with shared structure
Latent space models are frequently used for modeling singlelayer networ...
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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...
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Fast Network Community Detection with ProfilePseudo Likelihood Methods
The stochastic block model is one of the most studied network models for...
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Survival Analysis via Ordinary Differential Equations
This paper introduces a general framework for survival analysis based on...
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SODEN: A Scalable ContinuousTime Survival Model through Ordinary Differential Equation Networks
In this paper, we propose a flexible model for survival analysis using n...
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Community models for partially observed networks from surveys
Communities are a common and widely studied structure in networks, typic...
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NetworkAssisted Estimation for Largedimensional Factor Model with Guaranteed Convergence Rate Improvement
Network structure is growing popular for capturing the intrinsic relatio...
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MinorizationMaximizationbased Steepest Ascent for Largescale Survival Analysis with TimeVarying Effects: Application to the National Kidney Transplant Dataset
The timevarying effects model is a flexible and powerful tool for model...
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Highdimensional Gaussian graphical model for networklinked data
Graphical models are commonly used to represent conditional dependence r...
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A Flexible Generative Framework for Graphbased Semisupervised Learning
We consider a family of problems that are concerned about making predict...
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Online MultiObject Tracking with Dual Matching Attention Networks
In this paper, we propose an online MultiObject Tracking (MOT) approach...
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Model Selection and estimation of Multi Screen Penalty
We propose a multistep method, called Multi Screen Penalty (MSP), to es...
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CovarianceInsured Screening
Modern biotechnologies have produced a vast amount of highthroughput d...
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Link prediction for egocentrically sampled networks
Link prediction in networks is typically accomplished by estimating or r...
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Generalized linear models with low rank effects for network data
Networks are a useful representation for data on connections between uni...
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Classification with UltrahighDimensional Features
Although much progress has been made in classification with highdimensi...
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Estimating network edge probabilities by neighborhood smoothing
The estimation of probabilities of network edges from the observed adjac...
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Community Detection in Networks with Node Features
Many methods have been proposed for community detection in networks, but...
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Detecting Overlapping Communities in Networks Using Spectral Methods
Community detection is a fundamental problem in network analysis which i...
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Highdimensional Mixed Graphical Models
While graphical models for continuous data (Gaussian graphical models) a...
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Link prediction for partially observed networks
Link prediction is one of the fundamental problems in network analysis. ...
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Sparse Ising Models with Covariates
There has been a lot of work fitting Ising models to multivariate binary...
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Piecewise linear regularized solution paths
We consider the generic regularized optimization problem β̂(λ)=_βL(y,Xβ)...
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Ji Zhu
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