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Purnamrita Sarkar
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2020 – today
- 2024
- [i18]Syamantak Kumar, Purnamrita Sarkar, Peter J. Bickel, Derek Bean:
Keep or toss? A nonparametric score to evaluate solutions for noisy ICA. CoRR abs/2401.08468 (2024) - [i17]Syamantak Kumar, Purnamrita Sarkar:
Thresholded Oja does Sparse PCA? CoRR abs/2402.07240 (2024) - [i16]Akhil Jalan, Arya Mazumdar, Soumendu Sundar Mukherjee, Purnamrita Sarkar:
Transfer Learning for Latent Variable Network Models. CoRR abs/2406.03437 (2024) - [i15]Kamalika Chaudhuri, Po-Ling Loh, Shourya Pandey, Purnamrita Sarkar:
On Differentially Private U Statistics. CoRR abs/2407.04945 (2024) - [i14]Vansh Bansal, Saptarshi Roy, Purnamrita Sarkar, Alessandro Rinaldo:
Straightness of Rectified Flow: A Theoretical Insight into Wasserstein Convergence. CoRR abs/2410.14949 (2024) - 2023
- [j7]Prateek R. Srivastava
, Purnamrita Sarkar
A Robust Spectral Clustering Algorithm for Sub-Gaussian Mixture Models with Outliers. Oper. Res. 71(1): 224-244 (2023) - [c28]Syamantak Kumar, Purnamrita Sarkar:
Streaming PCA for Markovian Data. NeurIPS 2023 - [i13]Syamantak Kumar, Purnamrita Sarkar:
Streaming PCA for Markovian Data. CoRR abs/2305.02456 (2023) - 2022
- [i12]Nhat Ho, Tongzheng Ren, Sujay Sanghavi, Purnamrita Sarkar, Rachel A. Ward:
An Exponentially Increasing Step-size for Parameter Estimation in Statistical Models. CoRR abs/2205.07999 (2022) - [i11]Akhil Jalan, Deepayan Chakrabarti
Incentive-Aware Models of Dynamic Financial Networks. CoRR abs/2212.06808 (2022) - 2021
- [j6]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: 22:1-22:46 (2021) - [c27]Xueyu Mao
Consistent Nonparametric Methods for Network Assisted Covariate Estimation. ICML 2021: 7435-7446 - [c26]Robert Lunde, Purnamrita Sarkar, Rachel A. Ward:
Bootstrapping the Error of Oja's Algorithm. NeurIPS 2021: 6240-6252 - 2020
- [c25]Mingzhang Yin, Y. X. Rachel Wang, Purnamrita Sarkar:
A Theoretical Case Study of Structured Variational Inference for Community Detection. AISTATS 2020: 3750-3761 - [c24]Xinjie Fan, Yuguang Yue, Purnamrita Sarkar, Y. X. Rachel Wang
On hyperparameter tuning in general clustering problemsm. ICML 2020: 2996-3007 - [c23]Qiaohui Lin, Robert Lunde, Purnamrita Sarkar:
On the Theoretical Properties of the Network Jackknife. ICML 2020: 6105-6115
2010 – 2019
- 2019
- [i10]Xinjie Fan, Yuguang Yue, Purnamrita Sarkar, Y. X. Rachel Wang:
A Unified Framework for Tuning Hyperparameters in Clustering Problems. CoRR abs/1910.08018 (2019) - [i9]Prateek R. Srivastava, Purnamrita Sarkar, Grani A. Hanasusanto:
A Robust Spectral Clustering Algorithm for Sub-Gaussian Mixture Models with Outliers. CoRR abs/1912.07546 (2019) - 2018
- [c22]Bowei Yan, Purnamrita Sarkar, Xiuyuan Cheng:
Provable Estimation of the Number of Blocks in Block Models. AISTATS 2018: 1185-1194 - [c21]Xueyu Mao, Purnamrita Sarkar, Deepayan Chakrabarti:
Overlapping Clustering Models, and One (class) SVM to Bind Them All. NeurIPS 2018: 2130-2140 - [c20]Soumendu Sundar Mukherjee, Purnamrita Sarkar, Y. X. Rachel Wang, Bowei Yan:
Mean Field for the Stochastic Blockmodel: Optimization Landscape and Convergence Issues. NeurIPS 2018: 10717-10727 - [i8]Xueyu Mao, Purnamrita Sarkar, Deepayan Chakrabarti:
Overlapping Clustering Models, and One (class) SVM to Bind Them All. CoRR abs/1806.06945 (2018) - 2017
- [c19]Xueyu Mao
On Mixed Memberships and Symmetric Nonnegative Matrix Factorizations. ICML 2017: 2324-2333 - [c18]Bowei Yan, Mingzhang Yin, Purnamrita Sarkar:
Convergence of Gradient EM on Multi-component Mixture of Gaussians. NIPS 2017: 6956-6966 - [c17]Soumendu Sundar Mukherjee, Purnamrita Sarkar, Lizhen Lin:
On clustering network-valued data. NIPS 2017: 7071-7081 - [i7]Bowei Yan, Mingzhang Yin, Purnamrita Sarkar:
Statistical Convergence Analysis of Gradient EM on General Gaussian Mixture Models. CoRR abs/1705.08530 (2017) - [i6]Xueyu Mao, Purnamrita Sarkar, Deepayan Chakrabarti:
Estimating Mixed Memberships with Sharp Eigenvector Deviations. CoRR abs/1709.00407 (2017) - 2016
- [j5]Beth Trushkowsky, Tim Kraska, Michael J. Franklin, Purnamrita Sarkar:
Answering enumeration queries with the crowd. Commun. ACM 59(1): 118-127 (2016) - [c16]Bowei Yan, Purnamrita Sarkar:
On Robustness of Kernel Clustering. NIPS 2016: 3090-3098 - 2015
- [j4]Beth Trushkowsky, Tim Kraska, Michael J. Franklin, Purnamrita Sarkar, Venketaram Ramachandran:
Crowdsourcing Enumeration Queries: Estimators and Interfaces. IEEE Trans. Knowl. Data Eng. 27(7): 1796-1809 (2015) - [c15]Purnamrita Sarkar, Deepayan Chakrabarti, Peter J. Bickel:
The Consistency of Common Neighbors for Link Prediction in Stochastic Blockmodels. NIPS 2015: 3016-3024 - 2014
- [j3]Barzan Mozafari, Purnamrita Sarkar, Michael J. Franklin, Michael I. Jordan
Scaling Up Crowd-Sourcing to Very Large Datasets: A Case for Active Learning. Proc. VLDB Endow. 8(2): 125-136 (2014) - 2013
- [c14]Beth Trushkowsky, Tim Kraska, Michael J. Franklin, Purnamrita Sarkar:
Crowdsourced enumeration queries. ICDE 2013: 673-684 - [i5]Peter J. Bickel, Purnamrita Sarkar:
Hypothesis Testing for Automated Community Detection in Networks. CoRR abs/1311.2694 (2013) - 2012
- [c13]Ariel Kleiner, Ameet Talwalkar, Purnamrita Sarkar, Michael I. Jordan:
The Big Data Bootstrap. ICML 2012 - [c12]Purnamrita Sarkar, Deepayan Chakrabarti, Michael I. Jordan:
Nonparametric Link Prediction in Dynamic Networks. ICML 2012 - [i4]Beth Trushkowsky, Tim Kraska, Michael J. Franklin, Purnamrita Sarkar:
Getting It All from the Crowd. CoRR abs/1202.2335 (2012) - [i3]Purnamrita Sarkar, Andrew W. Moore:
A Tractable Approach to Finding Closest Truncated-commute-time Neighbors in Large Graphs. CoRR abs/1206.5259 (2012) - [i2]Barzan Mozafari, Purnamrita Sarkar, Michael J. Franklin, Michael I. Jordan, Samuel Madden:
Active Learning for Crowd-Sourced Databases. CoRR abs/1209.3686 (2012) - 2011
- [c11]Purnamrita Sarkar, Deepayan Chakrabarti
Theoretical Justification of Popular Link Prediction Heuristics. IJCAI 2011: 2722-2727 - [p1]Purnamrita Sarkar, Andrew W. Moore:
Random Walks in Social Networks and their Applications: A Survey. Social Network Data Analytics 2011: 43-77 - [i1]Purnamrita Sarkar, Deepayan Chakrabarti, Michael I. Jordan:
Non-parametric Link Prediction. CoRR abs/1109.1077 (2011) - 2010
- [c10]Purnamrita Sarkar, Deepayan Chakrabarti, Andrew W. Moore:
Theoretical Justification of Popular Link Prediction Heuristics. COLT 2010: 295-307 - [c9]Purnamrita Sarkar, Andrew W. Moore:
Fast nearest-neighbor search in disk-resident graphs. KDD 2010: 513-522
2000 – 2009
- 2009
- [c8]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: 125-130 - [c7]Purnamrita Sarkar, Andrew W. Moore:
Fast dynamic reranking in large graphs. WWW 2009: 31-40 - 2008
- [c6]Purnamrita Sarkar, Lujie Chen, Artur Dubrawski:
Dynamic Network Model for Predicting Occurrences of Salmonella at Food Facilities. BioSecure 2008: 56-63 - [c5]Purnamrita Sarkar, Andrew W. Moore, Amit Prakash:
Fast incremental proximity search in large graphs. ICML 2008: 896-903 - 2007
- [c4]Purnamrita Sarkar, Andrew W. Moore:
A Tractable Approach to Finding Closest Truncated-commute-time Neighbors in Large Graphs. UAI 2007: 335-343 - [c3]Purnamrita Sarkar, Sajid M. Siddiqi, Geoffrey J. Gordon:
A Latent Space Approach to Dynamic Embedding of Co-occurrence Data. AISTATS 2007: 420-427 - 2006
- [c2]Purnamrita Sarkar, Sajid M. Siddiqi, Geoffrey J. Gordon:
Approximate Kalman Filters for Embedding Author-Word Co-occurrence Data over Time. SNA@ICML 2006: 126-139 - 2005
- [j2]Jure Leskovec, Purnamrita Sarkar, Carlos Guestrin:
Modeling Link Qualities in a Sensor Network. Informatica (Slovenia) 29(4): 445-452 (2005) - [j1]Purnamrita Sarkar, Andrew W. Moore:
Dynamic social network analysis using latent space models. SIGKDD Explor. 7(2): 31-40 (2005) - [c1]Purnamrita Sarkar, Andrew W. Moore:
Dynamic Social Network Analysis using Latent Space Models. NIPS 2005: 1145-1152
Coauthor Index
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