Praneeth Netrapalli

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Prateek JainGoogle Research IndiaAdresse e-mail validée de google.com
Sham M KakadeHarvard UniversityAdresse e-mail validée de seas.harvard.edu
Chi JinAssistant Professor, Princeton UniversityAdresse e-mail validée de princeton.edu
Sujay SanghaviAssociate Professor, Electrical and Computer Engineering, WNCG, University of Texas, AustinAdresse e-mail validée de mail.utexas.edu
Rahul KidambiAmazon SearchAdresse e-mail validée de uw.edu
Aaron SidfordStanford UniversityAdresse e-mail validée de stanford.edu
Michael I. JordanProfessor of Electrical Engineering and Computer Sciences and Professor of Statistics, UC BerkeleyAdresse e-mail validée de cs.berkeley.edu
Rong GeDuke UniversityAdresse e-mail validée de cs.duke.edu
Dheeraj NagarajResearch Scientist, GoogleAdresse e-mail validée de google.com
Sewoong OhPaul G. Allen School of Computer Science and Engineering, University of WashingtonAdresse e-mail validée de cs.washington.edu
Kiran Koshy ThekumparampilAmazon AI, University of Illinois at Urbana-ChampaignAdresse e-mail validée de illinois.edu
Anima AnandkumarCalifornia Institute of Technology and NVIDIAAdresse e-mail validée de caltech.edu
Alekh AgarwalGoogleAdresse e-mail validée de google.com
Cameron MuscoAssistant Professor, University of Massachusetts AmherstAdresse e-mail validée de cs.umass.edu
Aravind RajeswaranFacebook AI Research (FAIR), UC BerkeleyAdresse e-mail validée de cs.washington.edu
Thorsten JoachimsProfessor of Computer Science, Cornell UniversityAdresse e-mail validée de cs.cornell.edu
Joe NeemanStatistics, UC BerkeleyAdresse e-mail validée de stat.berkeley.edu
Dan GarberAssistant Professor at Technion - Israel Institute of TechnologyAdresse e-mail validée de technion.ac.il
Rashish TandonAppleAdresse e-mail validée de apple.com
Niranjan Uma NareshAdresse e-mail validée de uci.edu

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Praneeth Netrapalli

Google Research

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Machine learning


Titre Trier par citations Trier par année Trier par titre	Citée par Citée par	Année
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	1094	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	740	2017
Phase retrieval using alternating minimization P Netrapalli, P Jain, S Sanghavi Advances in Neural Information Processing Systems 26, 2013	636	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	317	2020
Non-convex robust PCA P Netrapalli, N UN, S Sanghavi, A Anandkumar, P Jain Advances in neural information processing systems 27, 2014	315	2014
What is local optimality in nonconvex-nonconcave minimax optimization? C Jin, P Netrapalli, M Jordan International conference on machine learning, 4880-4889, 2020	280*	2020
Accelerated gradient descent escapes saddle points faster than gradient descent C Jin, P Netrapalli, MI Jordan Conference On Learning Theory, 1042-1085, 2018	236	2018
Learning the graph of epidemic cascades P Netrapalli, S Sanghavi ACM SIGMETRICS Performance Evaluation Review 40 (1), 211-222, 2012	209	2012
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	175	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	157*	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	152*	2018
Efficient algorithms for smooth minimax optimization KK Thekumparampil, P Jain, P Netrapalli, S Oh Advances in Neural Information Processing Systems 32, 2019	147	2019
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	142	2020
Information-theoretic thresholds for community detection in sparse networks J Banks, C Moore, J Neeman, P Netrapalli Conference on Learning Theory, 383-416, 2016	139*	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	134	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	127	2016
Learning sparsely used overcomplete dictionaries A Agarwal, A Anandkumar, P Jain, P Netrapalli, R Tandon Conference on Learning Theory, 123-137, 2014	116	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	112*	2016
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	108	2019
Fast exact matrix completion with finite samples P Jain, P Netrapalli Conference on Learning Theory, 1007-1034, 2015	105	2015

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