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04/18/2023
Independence testing for inhomogeneous random graphs
Testing for independence between graphs is a problem that arises natural...
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08/20/2022
Adversarial contamination of networks in the setting of vertex nomination: a new trimming method
As graph data becomes more ubiquitous, the need for robust inferential g...
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06/09/2022
Limit results for distributed estimation of invariant subspaces in multiple networks inference and PCA
We study the problem of estimating the left and right singular subspaces...
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03/19/2022
Perturbation Analysis of Randomized SVD and its Applications to High-dimensional Statistics
Randomized singular value decomposition (RSVD) is a class of computation...
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10/05/2021
Classification of high-dimensional data with spiked covariance matrix structure
We study the classification problem for high-dimensional data with n obs...
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09/09/2021
Popularity Adjusted Block Models are Generalized Random Dot Product Graphs
We connect two random graph models, the Popularity Adjusted Block Model ...
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05/23/2021
Hypothesis Testing for Equality of Latent Positions in Random Graphs
We consider the hypothesis testing problem that two vertices i and j of ...
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01/18/2021
Consistency of random-walk based network embedding algorithms
Random-walk based network embedding algorithms like node2vec and DeepWal...
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12/17/2020
Nonparametric Two-Sample Hypothesis Testing for Random Graphs with Negative and Repeated Eigenvalues
We propose a nonparametric two-sample test statistic for low-rank, condi...
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10/24/2020
Vertex nomination between graphs via spectral embedding and quadratic programming
Given a network and a subset of interesting vertices whose identities ar...
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08/03/2020
Two-sample Testing on Latent Distance Graphs With Unknown Link Functions
We propose a valid and consistent test for the hypothesis that two laten...
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04/15/2020
Learning 1-Dimensional Submanifolds for Subsequent Inference on Random Dot Product Graphs
A random dot product graph (RDPG) is a generative model for networks in ...
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03/31/2020
On Two Distinct Sources of Nonidentifiability in Latent Position Random Graph Models
Two separate and distinct sources of nonidentifiability arise naturally ...
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11/07/2019
Improving Power of 2-Sample Random Graph Tests with Applications in Connectomics
In many applications, there is an interest in testing whether two graphs...
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09/29/2019
Limit theorems for out-of-sample extensions of the adjacency and Laplacian spectral embeddings
Graph embeddings, a class of dimensionality reduction techniques designe...
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08/23/2018
On a 'Two Truths' Phenomenon in Spectral Graph Clustering
Clustering is concerned with coherently grouping observations without an...
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08/14/2018
On spectral embedding performance and elucidating network structure in stochastic block model graphs
Statistical inference on graphs often proceeds via spectral methods invo...
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06/04/2018
On estimation and inference in latent structure random graphs
We define a latent structure model (LSM) random graph as a random dot pr...
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04/02/2018
A Central Limit Theorem for Classical Multidimensional Scaling
Classical multidimensional scaling (CMDS) is a widely used method in man...
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03/30/2018
The eigenvalues of stochastic blockmodel graphs
We derive the limiting distribution for the largest eigenvalues of the a...
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02/01/2018
Signal-plus-noise matrix models: eigenvector deviations and fluctuations
Estimating eigenvectors and low-dimensional subspaces is of central impo...
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09/16/2017
The generalised random dot product graph
This paper introduces a latent position network model, called the genera...
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09/16/2017
Statistical inference on random dot product graphs: a survey
The random dot product graph (RDPG) is an independent-edge random graph ...
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09/05/2017
Linear Optimal Low Rank Projection for High-Dimensional Multi-Class Data
Classification of individual samples into one or more categories is crit...
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05/09/2017
Semiparametric spectral modeling of the Drosophila connectome
We present semiparametric spectral modeling of the complete larval Droso...
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07/28/2016
Limit theorems for eigenvectors of the normalized Laplacian for random graphs
We prove a central limit theorem for the components of the eigenvectors ...
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03/07/2015
Community Detection and Classification in Hierarchical Stochastic Blockmodels
We propose a robust, scalable, integrated methodology for community dete...
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05/23/2014
Empirical Bayes Estimation for the Stochastic Blockmodel
Inference for the stochastic blockmodel is currently of burgeoning inter...
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10/02/2013
Perfect Clustering for Stochastic Blockmodel Graphs via Adjacency Spectral Embedding
Vertex clustering in a stochastic blockmodel graph has wide applicabilit...
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05/31/2013
A central limit theorem for scaled eigenvectors of random dot product graphs
We prove a central limit theorem for the components of the largest eigen...
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05/21/2013
Out-of-sample Extension for Latent Position Graphs
We consider the problem of vertex classification for graphs constructed ...
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04/30/2013
Generalized Canonical Correlation Analysis for Classification
For multiple multivariate data sets, we derive conditions under which Ge...
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12/05/2012
Universally consistent vertex classification for latent positions graphs
In this work we show that, using the eigen-decomposition of the adjacenc...
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11/15/2012
Statistical inference on errorfully observed graphs
Statistical inference on graphs is a burgeoning field in the applied and...
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09/17/2012
Generalized Canonical Correlation Analysis for Disparate Data Fusion
Manifold matching works to identify embeddings of multiple disparate dat...
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07/29/2012
Universally Consistent Latent Position Estimation and Vertex Classification for Random Dot Product Graphs
In this work we show that, using the eigen-decomposition of the adjacenc...
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05/26/2012
On latent position inference from doubly stochastic messaging activities
We model messaging activities as a hierarchical doubly stochastic point ...
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08/10/2011
