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05/03/2023
Streaming PCA for Markovian Data
Since its inception in Erikki Oja's seminal paper in 1982, Oja's algorit...
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05/16/2022
An Exponentially Increasing Step-size for Parameter Estimation in Statistical Models
Using gradient descent (GD) with fixed or decaying step-size is standard...
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06/28/2021
Bootstrapping the error of Oja's Algorithm
We consider the problem of quantifying uncertainty for the estimation er...
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09/14/2020
Higher-Order Correct Multiplier Bootstraps for Count Functionals of Networks
Subgraph counts play a central role in both graph limit theory and netwo...
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04/19/2020
On the Theoretical Properties of the Network Jackknife
We study the properties of a leave-node-out jackknife procedure for netw...
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12/16/2019
A Robust Spectral Clustering Algorithm for Sub-Gaussian Mixture Models with Outliers
We consider the problem of clustering datasets in the presence of arbitr...
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10/17/2019
A Unified Framework for Tuning Hyperparameters in Clustering Problems
Selecting hyperparameters for unsupervised learning problems is difficul...
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07/29/2019
Subsampling Sparse Graphons Under Minimal Assumptions
We establish a general theory for subsampling network data generated by ...
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07/29/2019
A Theoretical Case Study of Structured Variational Inference for Community Detection
Mean-field variational inference (MFVI) has been widely applied in large...
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05/16/2019
When random initializations help: a study of variational inference for community detection
Variational approximation has been widely used in large-scale Bayesian i...
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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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06/18/2018
Overlapping Clustering Models, and One (class) SVM to Bind Them All
People belong to multiple communities, words belong to multiple topics, ...
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09/01/2017
Estimating Mixed Memberships with Sharp Eigenvector Deviations
We consider the problem of estimating overlapping community memberships....
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08/18/2017
Two provably consistent divide and conquer clustering algorithms for large networks
In this article, we advance divide-and-conquer strategies for solving th...
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05/24/2017
Provable Estimation of the Number of Blocks in Block Models
Community detection is a fundamental unsupervised learning problem for u...
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07/10/2016
Convex Relaxation for Community Detection with Covariates
Community detection in networks is an important problem in many applied ...
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07/01/2016
On Mixed Memberships and Symmetric Nonnegative Matrix Factorizations
The problem of finding overlapping communities in networks has gained mu...
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06/08/2016
On clustering network-valued data
Community detection, which focuses on clustering nodes or detecting comm...
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06/06/2016
On Robustness of Kernel Clustering
Clustering is one of the most important unsupervised problems in machine...
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11/12/2013
Hypothesis Testing for Automated Community Detection in Networks
Community detection in networks is a key exploratory tool with applicati...
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10/05/2013
Role of normalization in spectral clustering for stochastic blockmodels
Spectral clustering is a technique that clusters elements using the top ...
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06/27/2012
The Big Data Bootstrap
The bootstrap provides a simple and powerful means of assessing the qual...
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06/27/2012
Nonparametric Link Prediction in Dynamic Networks
We propose a non-parametric link prediction algorithm for a sequence of ...
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12/21/2011
A Scalable Bootstrap for Massive Data
The bootstrap provides a simple and powerful means of assessing the qual...
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09/06/2011