Purnamrita Sarkar | DeepAI

DeepAI

Featured Co-authors

Michael I. Jordan
268 publications
Nhat Ho
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Sujay Sanghavi
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Ameet Talwalkar
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Rachel Ward
39 publications
Lizhen Lin
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Xiuyuan Cheng
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Elizaveta Levina
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Tongzheng Ren
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Peter J. Bickel
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Michael Jordan
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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...

Nhat Ho, et al. ∙

∙ 06/28/2021

Bootstrapping the error of Oja's Algorithm

We consider the problem of quantifying uncertainty for the estimation er...

Robert Lunde, et al. ∙

∙ 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...

Qiaohui Lin, et al. ∙

∙ 04/19/2020

On the Theoretical Properties of the Network Jackknife

We study the properties of a leave-node-out jackknife procedure for netw...

Qiaohui Lin, et al. ∙

∙ 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...

Prateek R. Srivastava, et al. ∙

∙ 10/17/2019

A Unified Framework for Tuning Hyperparameters in Clustering Problems

Selecting hyperparameters for unsupervised learning problems is difficul...

Xinjie Fan, et al. ∙

∙ 07/29/2019

Subsampling Sparse Graphons Under Minimal Assumptions

We establish a general theory for subsampling network data generated by ...

Robert Lunde, et al. ∙

∙ 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...

Mingzhang Yin, et al. ∙

∙ 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...

Purnamrita Sarkar, et al. ∙

∙ 10/02/2018

Hierarchical community detection by recursive bi-partitioning

The problem of community detection in networks is usually formulated as ...

Tianxi Li, et al. ∙

∙ 06/18/2018

Overlapping Clustering Models, and One (class) SVM to Bind Them All

People belong to multiple communities, words belong to multiple topics, ...

Xueyu Mao, et al. ∙

∙ 09/01/2017

Estimating Mixed Memberships with Sharp Eigenvector Deviations

We consider the problem of estimating overlapping community memberships....

Xueyu Mao, et al. ∙

∙ 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...

Soumendu Sundar Mukherjee, et al. ∙

∙ 05/24/2017

Provable Estimation of the Number of Blocks in Block Models

Community detection is a fundamental unsupervised learning problem for u...

Bowei Yan, et al. ∙

∙ 07/10/2016

Convex Relaxation for Community Detection with Covariates

Community detection in networks is an important problem in many applied ...

Bowei Yan, et al. ∙

∙ 07/01/2016

On Mixed Memberships and Symmetric Nonnegative Matrix Factorizations

The problem of finding overlapping communities in networks has gained mu...

Xueyu Mao, et al. ∙

∙ 06/08/2016

On clustering network-valued data

Community detection, which focuses on clustering nodes or detecting comm...

Soumendu Sundar Mukherjee, et al. ∙

∙ 06/06/2016

On Robustness of Kernel Clustering

Clustering is one of the most important unsupervised problems in machine...

Bowei Yan, et al. ∙

∙ 11/12/2013

Hypothesis Testing for Automated Community Detection in Networks

Community detection in networks is a key exploratory tool with applicati...

Peter J. Bickel, et al. ∙

∙ 10/05/2013

Role of normalization in spectral clustering for stochastic blockmodels

Spectral clustering is a technique that clusters elements using the top ...

Purnamrita Sarkar, et al. ∙

∙ 06/27/2012

The Big Data Bootstrap

The bootstrap provides a simple and powerful means of assessing the qual...

Ariel Kleiner, et al. ∙

∙ 06/27/2012

Nonparametric Link Prediction in Dynamic Networks

We propose a non-parametric link prediction algorithm for a sequence of ...

Purnamrita Sarkar, et al. ∙

∙ 12/21/2011

A Scalable Bootstrap for Massive Data

The bootstrap provides a simple and powerful means of assessing the qual...

Ariel Kleiner, et al. ∙

∙ 09/06/2011

Nonparametric Link Prediction in Large Scale Dynamic Networks

We propose a nonparametric approach to link prediction in large-scale dy...

Purnamrita Sarkar, et al. ∙