Praneeth Netrapalli

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Prateek JainGoogle Research IndiaVerified email at google.com
Sham M KakadeHarvard UniversityVerified email at seas.harvard.edu
Chi JinAssistant Professor, Princeton UniversityVerified email at princeton.edu
Sujay SanghaviAssociate Professor, Electrical and Computer Engineering, University of Texas, AustinVerified email at mail.utexas.edu
Rahul KidambiAmazon SearchVerified email at uw.edu
Aaron SidfordStanford UniversityVerified email at stanford.edu
Michael I. JordanProfessor of Electrical Engineering and Computer Sciences and Professor of Statistics, UC BerkeleyVerified email at cs.berkeley.edu
Rong GeDuke UniversityVerified email at cs.duke.edu
Dheeraj NagarajResearch Scientist, GoogleVerified email at google.com
Sewoong OhPaul G. Allen School of Computer Science and Engineering, University of WashingtonVerified email at cs.washington.edu
Kiran Koshy ThekumparampilAmazon AI, University of Illinois at Urbana-ChampaignVerified email at illinois.edu
Anima AnandkumarCalifornia Institute of Technology and NVIDIAVerified email at caltech.edu
Alekh AgarwalGoogleVerified email at google.com
Cameron MuscoAssistant Professor, University of Massachusetts AmherstVerified email at cs.umass.edu
Aravind RajeswaranMeta PlatformsVerified email at cs.washington.edu
Thorsten JoachimsProfessor of Computer Science, Cornell UniversityVerified email at cs.cornell.edu
Joe NeemanStatistics, UC BerkeleyVerified email at stat.berkeley.edu
Dan GarberAssociate Professor at Technion - Israel Institute of TechnologyVerified email at technion.ac.il
Rashish TandonAppleVerified email at apple.com
Niranjan Uma NareshVerified email at uci.edu

Praneeth Netrapalli

Google Research

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Machine learning


Title Sort by citations Sort by year Sort by title	Cited by Cited by	Year
Low-rank matrix completion using alternating minimization P Jain, P Netrapalli, S Sanghavi Proceedings of the forty-fifth annual ACM symposium on Theory of computing …, 2013	1120	2013
How to escape saddle points efficiently C Jin, R Ge, P Netrapalli, SM Kakade, MI Jordan International conference on machine learning, 1724-1732, 2017	795	2017
Phase retrieval using alternating minimization P Netrapalli, P Jain, S Sanghavi Advances in Neural Information Processing Systems 26, 2013	653	2013
Morel: Model-based offline reinforcement learning R Kidambi, A Rajeswaran, P Netrapalli, T Joachims Advances in neural information processing systems 33, 21810-21823, 2020	392	2020
Non-convex robust PCA P Netrapalli, N UN, S Sanghavi, A Anandkumar, P Jain Advances in neural information processing systems 27, 2014	326	2014
What is local optimality in nonconvex-nonconcave minimax optimization? C Jin, P Netrapalli, M Jordan International conference on machine learning, 4880-4889, 2020	318*	2020
Accelerated gradient descent escapes saddle points faster than gradient descent C Jin, P Netrapalli, MI Jordan Conference On Learning Theory, 1042-1085, 2018	246	2018
Learning the graph of epidemic cascades P Netrapalli, S Sanghavi ACM SIGMETRICS Performance Evaluation Review 40 (1), 211-222, 2012	214	2012
The pitfalls of simplicity bias in neural networks H Shah, K Tamuly, A Raghunathan, P Jain, P Netrapalli Advances in Neural Information Processing Systems 33, 9573-9585, 2020	193	2020
Learning sparsely used overcomplete dictionaries via alternating minimization A Agarwal, A Anandkumar, P Jain, P Netrapalli SIAM Journal on Optimization 26 (4), 2775-2799, 2016	182	2016
On nonconvex optimization for machine learning: Gradients, stochasticity, and saddle points C Jin, P Netrapalli, R Ge, SM Kakade, MI Jordan Journal of the ACM (JACM) 68 (2), 1-29, 2021	169*	2021
Parallelizing stochastic gradient descent for least squares regression: mini-batching, averaging, and model misspecification P Jain, S Kakade, R Kidambi, P Netrapalli, A Sidford Journal of Machine Learning Research 18, 2018	162*	2018
Efficient algorithms for smooth minimax optimization KK Thekumparampil, P Jain, P Netrapalli, S Oh Advances in Neural Information Processing Systems 32, 2019	161	2019
Information-theoretic thresholds for community detection in sparse networks J Banks, C Moore, J Neeman, P Netrapalli Conference on Learning Theory, 383-416, 2016	147*	2016
Accelerating stochastic gradient descent for least squares regression P Jain, SM Kakade, R Kidambi, P Netrapalli, A Sidford Conference On Learning Theory, 545-604, 2018	142	2018
Streaming pca: Matching matrix bernstein and near-optimal finite sample guarantees for oja’s algorithm P Jain, C Jin, SM Kakade, P Netrapalli, A Sidford Conference on learning theory, 1147-1164, 2016	136	2016
Efficient domain generalization via common-specific low-rank decomposition V Piratla, P Netrapalli, S Sarawagi International Conference on Machine Learning, 7728-7738, 2020	129	2020
The step decay schedule: A near optimal, geometrically decaying learning rate procedure for least squares R Ge, SM Kakade, R Kidambi, P Netrapalli Advances in neural information processing systems 32, 2019	118	2019
Learning sparsely used overcomplete dictionaries A Agarwal, A Anandkumar, P Jain, P Netrapalli, R Tandon Conference on Learning Theory, 123-137, 2014	117	2014
Faster eigenvector computation via shift-and-invert preconditioning D Garber, E Hazan, C Jin, C Musco, P Netrapalli, A Sidford International Conference on Machine Learning, 2626-2634, 2016	116*	2016

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