Purnamrita Sarkar

Publication Activity (10 Years)

Years Active: 2005-2024
Publications (10 Years): 28

Top Topics

Gaussian Mixture

Top Venues

Publications

Syamantak Kumar, Purnamrita Sarkar, Peter J. Bickel, Derek Bean
Keep or toss? A nonparametric score to evaluate solutions for noisy ICA. CoRR (2024)
Syamantak Kumar, Purnamrita Sarkar
Thresholded Oja does Sparse PCA? CoRR (2024)
Akhil Jalan, Arya Mazumdar, Soumendu Sundar Mukherjee, Purnamrita Sarkar
Transfer Learning for Latent Variable Network Models. CoRR (2024)
Kamalika Chaudhuri, Po-Ling Loh, Shourya Pandey, Purnamrita Sarkar
On Differentially Private U Statistics. CoRR (2024)
Syamantak Kumar, Purnamrita Sarkar
Streaming PCA for Markovian Data. CoRR (2023)
Prateek R. Srivastava, Purnamrita Sarkar, Grani A. Hanasusanto
A Robust Spectral Clustering Algorithm for Sub-Gaussian Mixture Models with Outliers. Oper. Res. 71 (1) (2023)
Syamantak Kumar, Purnamrita Sarkar
Streaming PCA for Markovian Data. NeurIPS (2023)
Akhil Jalan, Deepayan Chakrabarti, Purnamrita Sarkar
Incentive-Aware Models of Dynamic Financial Networks. CoRR (2022)
Nhat Ho, Tongzheng Ren, Sujay Sanghavi, Purnamrita Sarkar, Rachel Ward
An Exponentially Increasing Step-size for Parameter Estimation in Statistical Models. CoRR (2022)
Robert Lunde, Purnamrita Sarkar, Rachel Ward
Bootstrapping the Error of Oja's Algorithm. NeurIPS (2021)
Purnamrita Sarkar, Y. X. Rachel Wang, Soumendu Sundar Mukherjee
When random initializations help: a study of variational inference for community detection. J. Mach. Learn. Res. 22 (2021)
Xueyu Mao, Deepayan Chakrabarti, Purnamrita Sarkar
Consistent Nonparametric Methods for Network Assisted Covariate Estimation. ICML (2021)
Qiaohui Lin, Robert Lunde, Purnamrita Sarkar
On the Theoretical Properties of the Network Jackknife. ICML (2020)
Mingzhang Yin, Y. X. Rachel Wang, Purnamrita Sarkar
A Theoretical Case Study of Structured Variational Inference for Community Detection. AISTATS (2020)
Xinjie Fan, Yuguang Yue, Purnamrita Sarkar, Y. X. Rachel Wang
On hyperparameter tuning in general clustering problemsm. ICML (2020)
Prateek R. Srivastava, Purnamrita Sarkar, Grani A. Hanasusanto
A Robust Spectral Clustering Algorithm for Sub-Gaussian Mixture Models with Outliers. CoRR (2019)
Xinjie Fan, Yuguang Yue, Purnamrita Sarkar, Y. X. Rachel Wang
A Unified Framework for Tuning Hyperparameters in Clustering Problems. CoRR (2019)
Xueyu Mao, Purnamrita Sarkar, Deepayan Chakrabarti
Overlapping Clustering Models, and One (class) SVM to Bind Them All. NeurIPS (2018)
Xueyu Mao, Purnamrita Sarkar, Deepayan Chakrabarti
Overlapping Clustering Models, and One (class) SVM to Bind Them All. CoRR (2018)
Bowei Yan, Purnamrita Sarkar, Xiuyuan Cheng
Provable Estimation of the Number of Blocks in Block Models. AISTATS (2018)
Soumendu Sundar Mukherjee, Purnamrita Sarkar, Y. X. Rachel Wang, Bowei Yan
Mean Field for the Stochastic Blockmodel: Optimization Landscape and Convergence Issues. NeurIPS (2018)
Xueyu Mao, Purnamrita Sarkar, Deepayan Chakrabarti
On Mixed Memberships and Symmetric Nonnegative Matrix Factorizations. ICML (2017)
Bowei Yan, Mingzhang Yin, Purnamrita Sarkar
Statistical Convergence Analysis of Gradient EM on General Gaussian Mixture Models. CoRR (2017)
Bowei Yan, Mingzhang Yin, Purnamrita Sarkar
Convergence of Gradient EM on Multi-component Mixture of Gaussians. NIPS (2017)
Soumendu Sundar Mukherjee, Purnamrita Sarkar, Lizhen Lin
On clustering network-valued data. NIPS (2017)
Xueyu Mao, Purnamrita Sarkar, Deepayan Chakrabarti
Estimating Mixed Memberships with Sharp Eigenvector Deviations. CoRR (2017)
Bowei Yan, Purnamrita Sarkar
On Robustness of Kernel Clustering. NIPS (2016)
Beth Trushkowsky, Tim Kraska, Michael J. Franklin, Purnamrita Sarkar
Answering enumeration queries with the crowd. Commun. ACM 59 (1) (2016)
Purnamrita Sarkar, Deepayan Chakrabarti, Peter J. Bickel
The Consistency of Common Neighbors for Link Prediction in Stochastic Blockmodels. NIPS (2015)
Beth Trushkowsky, Tim Kraska, Michael J. Franklin, Purnamrita Sarkar, Venketaram Ramachandran
Crowdsourcing Enumeration Queries: Estimators and Interfaces. IEEE Trans. Knowl. Data Eng. 27 (7) (2015)
Barzan Mozafari, Purnamrita Sarkar, Michael J. Franklin, Michael I. Jordan, Samuel Madden
Scaling Up Crowd-Sourcing to Very Large Datasets: A Case for Active Learning. Proc. VLDB Endow. 8 (2) (2014)
Beth Trushkowsky, Tim Kraska, Michael J. Franklin, Purnamrita Sarkar
Crowdsourced enumeration queries. ICDE (2013)
Peter J. Bickel, Purnamrita Sarkar
Hypothesis Testing for Automated Community Detection in Networks. CoRR (2013)
Ariel Kleiner, Ameet Talwalkar, Purnamrita Sarkar, Michael I. Jordan
The Big Data Bootstrap. ICML (2012)
Purnamrita Sarkar, Deepayan Chakrabarti, Michael I. Jordan
Nonparametric Link Prediction in Dynamic Networks. ICML (2012)
Barzan Mozafari, Purnamrita Sarkar, Michael J. Franklin, Michael I. Jordan, Samuel Madden
Active Learning for Crowd-Sourced Databases CoRR (2012)
Beth Trushkowsky, Tim Kraska, Michael J. Franklin, Purnamrita Sarkar
Getting It All from the Crowd CoRR (2012)
Purnamrita Sarkar, Andrew W. Moore
A Tractable Approach to Finding Closest Truncated-commute-time Neighbors in Large Graphs CoRR (2012)
Purnamrita Sarkar, Deepayan Chakrabarti, Michael I. Jordan
Non-parametric Link Prediction CoRR (2011)
Purnamrita Sarkar, Deepayan Chakrabarti, Andrew W. Moore
Theoretical Justification of Popular Link Prediction Heuristics. IJCAI (2011)
Purnamrita Sarkar, Deepayan Chakrabarti, Andrew W. Moore
Theoretical Justification of Popular Link Prediction Heuristics. COLT (2010)
Purnamrita Sarkar, Andrew W. Moore
Fast nearest-neighbor search in disk-resident graphs. KDD (2010)
Purnamrita Sarkar, Andrew W. Moore
Fast dynamic reranking in large graphs. WWW (2009)
Artur Dubrawski, Purnamrita Sarkar, Lujie Chen
Trade-offs between Agility and Reliability of Predictions in Dynamic Social Networks Used to Model Risk of Microbial Contamination of Food. ASONAM (2009)
Purnamrita Sarkar, Andrew W. Moore, Amit Prakash
Fast incremental proximity search in large graphs. ICML (2008)
Purnamrita Sarkar, Lujie Chen, Artur Dubrawski
Dynamic Network Model for Predicting Occurrences of Salmonella at Food Facilities. BioSecure (2008)
Purnamrita Sarkar, Sajid M. Siddiqi, Geoffrey J. Gordon
A Latent Space Approach to Dynamic Embedding of Co-occurrence Data. AISTATS (2007)
Purnamrita Sarkar, Andrew W. Moore
A Tractable Approach to Finding Closest Truncated-commute-time Neighbors in Large Graphs. UAI (2007)
Purnamrita Sarkar, Sajid M. Siddiqi, Geoffrey J. Gordon
Approximate Kalman Filters for Embedding Author-Word Co-occurrence Data over Time. SNA@ICML (2006)
Purnamrita Sarkar, Andrew W. Moore
Dynamic social network analysis using latent space models. SIGKDD Explor. 7 (2) (2005)
Jure Leskovec, Purnamrita Sarkar, Carlos Guestrin
Modeling Link Qualities in a Sensor Network. Informatica (Slovenia) 29 (4) (2005)
Purnamrita Sarkar, Andrew W. Moore
Dynamic Social Network Analysis using Latent Space Models. NIPS (2005)