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08/22/2023
Computational Inference for Directions in Canonical Correlation Analysis
Canonical Correlation Analysis (CCA) is a method for analyzing pairs of ...
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05/15/2023
Fair Information Spread on Social Networks with Community Structure
Information spread through social networks is ubiquitous. Influence maxi...
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03/10/2023
A pseudo-likelihood approach to community detection in weighted networks
Community structure is common in many real networks, with nodes clustere...
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02/20/2023
Conformal Prediction for Network-Assisted Regression
An important problem in network analysis is predicting a node attribute ...
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10/31/2022
Prediction of Network Covariates Using Edge and Node Attributes
In this work we consider the setting where many networks are observed on...
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10/14/2022
Latent process models for functional network data
Network data are often sampled with auxiliary information or collected t...
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06/27/2022
Network resampling for estimating uncertainty
With network data becoming ubiquitous in many applications, many models ...
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05/27/2022
Selective Inference for Sparse Multitask Regression with Applications in Neuroimaging
Multi-task learning is frequently used to model a set of related respons...
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12/28/2020
Latent space models for multiplex networks with shared structure
Latent space models are frequently used for modeling single-layer networ...
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09/20/2020
Overlapping community detection in networks via sparse spectral decomposition
We consider the problem of estimating overlapping community memberships ...
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08/09/2020
Community models for partially observed networks from surveys
Communities are a common and widely studied structure in networks, typic...
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02/05/2020
Simultaneous prediction and community detection for networks with application to neuroimaging
Community structure in networks is observed in many different domains, a...
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10/16/2019
Matrix Means and a Novel High-Dimensional Shrinkage Phenomenon
Many statistical settings call for estimating a population parameter, mo...
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07/25/2019
Bootstrapping Networks with Latent Space Structure
A core problem in statistical network analysis is to develop network ana...
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07/04/2019
High-dimensional Gaussian graphical model for network-linked data
Graphical models are commonly used to represent conditional dependence r...
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06/13/2019
Recovering low-rank structure from multiple networks with unknown edge distributions
In increasingly many settings, particularly in neuroimaging, data sets c...
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03/06/2019
Graph-aware linear mixed effects models for brain connectivity networks
Neuroimaging data on functional connections in the brain are frequently ...
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03/06/2019
Graph-aware Modeling of Brain Connectivity Networks
Functional connections in the brain are frequently represented by weight...
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10/02/2018
Hierarchical community detection by recursive bi-partitioning
The problem of community detection in networks is usually formulated as ...
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03/12/2018
Link prediction for egocentrically sampled networks
Link prediction in networks is typically accomplished by estimating or r...
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01/26/2018
Concentration of random graphs and application to community detection
Random matrix theory has played an important role in recent work on stat...
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10/13/2017
Estimating a network from multiple noisy realizations
Complex interactions between entities are often represented as edges in ...
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05/18/2017
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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01/27/2017
Network classification with applications to brain connectomics
While statistical analysis of a single network has received a lot of att...
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09/29/2015
Estimating network edge probabilities by neighborhood smoothing
The estimation of probabilities of network edges from the observed adjac...
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09/03/2015
Community Detection in Networks with Node Features
Many methods have been proposed for community detection in networks, but...
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07/03/2015
Estimating the number of communities in networks by spectral methods
Community detection is a fundamental problem in network analysis with ma...
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12/10/2014
Detecting Overlapping Communities in Networks Using Spectral Methods
Community detection is a fundamental problem in network analysis which i...
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06/21/2014
On semidefinite relaxations for the block model
The stochastic block model (SBM) is a popular tool for community detecti...
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05/31/2014
Optimization via Low-rank Approximation for Community Detection in Networks
Community detection is one of the fundamental problems of network analys...
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04/09/2013
High-dimensional Mixed Graphical Models
While graphical models for continuous data (Gaussian graphical models) a...
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01/29/2013
Link prediction for partially observed networks
Link prediction is one of the fundamental problems in network analysis. ...
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09/27/2012
Sparse Ising Models with Covariates
There has been a lot of work fitting Ising models to multivariate binary...
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07/10/2012