Purnamrita Sarkar

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Andrew MooreDean, School of Computer Science, Carnegie MellonVerified email at cs.cmu.edu
Michael I. JordanProfessor of Electrical Engineering and Computer Sciences and Professor of Statistics, UC BerkeleyVerified email at cs.berkeley.edu
Deepayan ChakrabartiAssistant Professor, McCombs School of Business, UT AustinVerified email at utexas.edu
peter bickelProfessor of Statistics, UC BerkeleyVerified email at stat.berkeley.edu
Michael FranklinLiew Family Chair of Computer Science, University of ChicagoVerified email at uchicago.edu
Bowei YanUniversity of Texas at AustinVerified email at utexas.edu
Ameet TalwalkarCMU and Determined AIVerified email at cmu.edu
Xueyu Mao (毛学宇)The University of Texas at AustinVerified email at cs.utexas.edu
Tim KraskaMITVerified email at mit.edu
Soumendu Sundar MukherjeeINSPIRE Faculty at ISRU at ISI, KolkataVerified email at berkeley.edu
Samuel MaddenMITVerified email at csail.mit.edu
Barzan MozafariAssociate Professor, University of Michigan (Ann Arbor)Verified email at umich.edu
Y. X. Rachel WangSchool of Mathematics and Statistics, University of SydneyVerified email at sydney.edu.au
Mingzhang YinData Science Institute, Columbia UniversityVerified email at columbia.edu
Sajid SiddiqiGoogleVerified email at google.com
Lizhen LinDepartment of Applied and Computational Mathematics and Statistics, The University of Notre DameVerified email at nd.edu
Sharmodeep BhattacharyyaAssistant Professor of Statistics, Oregon State UniversityVerified email at science.oregonstate.edu
Tianxi LiAssistant Professor of Statistics, University of VirginiaVerified email at virginia.edu
Koen Van den BergePostdoctoral researcher, University of California, Berkeley and Ghent UniversityVerified email at berkeley.edu
LIHUA LEIPostdoctoral researcher in statistics, Stanford UniversityVerified email at stanford.edu

Purnamrita Sarkar

Assistant Professor, Statistics and Data Sciences, University of Texas at Austin

Verified email at austin.utexas.edu

Theoretical Statistics Scalable Algorithms Networks Machine Learning Random Matrices


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Dynamic social network analysis using latent space models P Sarkar, A Moore Advances in Neural Information Processing Systems 18, 2005	408	2005
A scalable bootstrap for massive data A Kleiner, A Talwalkar, P Sarkar, MI Jordan Journal of the Royal Statistical Society: Series B (Statistical Methodology …, 2014	400	2014
Scaling up crowd-sourcing to very large datasets: a case for active learning B Mozafari, P Sarkar, M Franklin, M Jordan, S Madden Proceedings of the VLDB Endowment 8 (2), 125-136, 2014	199	2014
The big data bootstrap A Kleiner, A Talwalkar, P Sarkar, M Jordan arXiv preprint arXiv:1206.6415, 2012	167	2012
Nonparametric link prediction in dynamic networks P Sarkar, D Chakrabarti, M Jordan arXiv preprint arXiv:1206.6394, 2012	166	2012
Hypothesis testing for automated community detection in networks PJ Bickel, P Sarkar Journal of the Royal Statistical Society: Series B (Statistical Methodology …, 2016	157	2016
Crowdsourced enumeration queries B Trushkowsky, T Kraska, MJ Franklin, P Sarkar 2013 IEEE 29th International Conference on Data Engineering (ICDE), 673-684, 2013	120	2013
Fast incremental proximity search in large graphs P Sarkar, AW Moore, A Prakash Proceedings of the 25th international conference on Machine learning, 896-903, 2008	120	2008
Theoretical justification of popular link prediction heuristics P Sarkar, D Chakrabarti, AW Moore Twenty-Second International Joint Conference on Artificial Intelligence, 2011	116	2011
Dynamic social network analysis using latent space models P Sarkar, AW Moore Advances in neural information processing systems 18, 1145, 2006	111	2006
A tractable approach to finding closest truncated-commute-time neighbors in large graphs P Sarkar, A Moore arXiv preprint arXiv:1206.5259, 2012	102	2012
Role of normalization in spectral clustering for stochastic blockmodels P Sarkar, PJ Bickel The Annals of Statistics 43 (3), 962-990, 2015	101	2015
A latent space approach to dynamic embedding of co-occurrence data P Sarkar, SM Siddiqi, GJ Gordon Artificial Intelligence and Statistics, 420-427, 2007	81	2007
Fast nearest-neighbor search in disk-resident graphs P Sarkar, AW Moore Proceedings of the 16th ACM SIGKDD international conference on Knowledge …, 2010	69	2010
Estimating mixed memberships with sharp eigenvector deviations X Mao, P Sarkar, D Chakrabarti Journal of the American Statistical Association 116 (536), 1928-1940, 2021	56*	2021
Covariate regularized community detection in sparse graphs B Yan, P Sarkar Journal of the American Statistical Association 116 (534), 734-745, 2021	53*	2021
Active learning for crowd-sourced databases B Mozafari, P Sarkar, MJ Franklin, MI Jordan, S Madden arXiv preprint arXiv:1209.3686, 2012	51	2012
Convergence of gradient EM on multi-component mixture of Gaussians B Yan, M Yin, P Sarkar Advances in Neural Information Processing Systems 30, 2017	44*	2017
On mixed memberships and symmetric nonnegative matrix factorizations X Mao, P Sarkar, D Chakrabarti International Conference on Machine Learning, 2324-2333, 2017	43	2017
Hierarchical community detection by recursive partitioning T Li, L Lei, S Bhattacharyya, K Van den Berge, P Sarkar, PJ Bickel, ... Journal of the American Statistical Association 117 (538), 951-968, 2022	33	2022

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