
Overlapping community detection in networks via sparse spectral decomposition
We consider the problem of estimating overlapping community memberships ...
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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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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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Matrix Means and a Novel HighDimensional Shrinkage Phenomenon
Many statistical settings call for estimating a population parameter, mo...
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Bootstrapping Networks with Latent Space Structure
A core problem in statistical network analysis is to develop network ana...
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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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Recovering lowrank structure from multiple networks with unknown edge distributions
In increasingly many settings, particularly in neuroimaging, data sets c...
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Graphaware linear mixed effects models for brain connectivity networks
Neuroimaging data on functional connections in the brain are frequently ...
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Graphaware Modeling of Brain Connectivity Networks
Functional connections in the brain are frequently represented by weight...
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Hierarchical community detection by recursive bipartitioning
The problem of community detection in networks is usually formulated as ...
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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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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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Estimating a network from multiple noisy realizations
Complex interactions between entities are often represented as edges in ...
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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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Network classification with applications to brain connectomics
While statistical analysis of a single network has received a lot of att...
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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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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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Detecting Overlapping Communities in Networks Using Spectral Methods
Community detection is a fundamental problem in network analysis which i...
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On semidefinite relaxations for the block model
The stochastic block model (SBM) is a popular tool for community detecti...
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Optimization via Lowrank Approximation for Community Detection in Networks
Community detection is one of the fundamental problems of network analys...
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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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Pseudolikelihood methods for community detection in large sparse networks
Many algorithms have been proposed for fitting network models with commu...
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