Srinadh Bhojanapalli

Citirano

	Sve	Od 2018.
Citati	4574	4192
H-indeks	23	20
i10-indeks	28	26

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Behnam NeyshaburSenior Staff Research Scientist, DeepMindPotvrđena adresa e-pošte na google.com
Nathan SrebroProfessor, TTIC and University of ChicagoPotvrđena adresa e-pošte na ttic.edu
Sujay SanghaviAssociate Professor, Electrical and Computer Engineering, WNCG, University of Texas, AustinPotvrđena adresa e-pošte na mail.utexas.edu
Anastasios KyrillidisAssistant Professor, Computer Science Department, Rice UniversityPotvrđena adresa e-pošte na rice.edu
Ayan ChakrabartiGoogle ResearchPotvrđena adresa e-pošte na google.com
Rachel WardUT AustinPotvrđena adresa e-pošte na math.utexas.edu
Prateek JainGoogle Research IndiaPotvrđena adresa e-pošte na google.com
Zhiyuan LiPostdoc, Stanford UniversityPotvrđena adresa e-pošte na stanford.edu
Yudong ChenAssociate Professor, University of Wisconsin-MadisonPotvrđena adresa e-pošte na wisc.edu
Yann LeCunChief AI Scientist at Facebook & Silver Professor at the Courant Institute, New York UniversityPotvrđena adresa e-pošte na cs.nyu.edu
Constantine CaramanisProfessor of Electrical and Computer Engineering, UT AustinPotvrđena adresa e-pošte na utexas.edu
Dohyung ParkThe University of Texas at AustinPotvrđena adresa e-pošte na utexas.edu
Amir KalevInformation Sciences Institute, University of Southern CaliforniaPotvrđena adresa e-pošte na isi.edu
Praneeth NetrapalliGoogle ResearchPotvrđena adresa e-pošte na google.com
Nicolas BoumalEcole Polytechnique Fédérale de Lausanne (EPFL)Potvrđena adresa e-pošte na epfl.ch
Alexandros G DimakisProfessor, ECE University of Texas at AustinPotvrđena adresa e-pošte na austin.utexas.edu
David McAllesterProfessor, Toyota Technological Institute at ChicagoPotvrđena adresa e-pošte na ttic.edu

Prati

Srinadh Bhojanapalli

Research Scientist, Google Research

Potvrđena adresa e-pošte na google.com - Početna stranica

Machine learning Algorithms


Naslov Poredaj po navodima Poredaj po godini Poredaj po naslovu	Citirano Citirano	Godina
Exploring generalization in deep learning B Neyshabur, S Bhojanapalli, D McAllester, N Srebro Advances in neural information processing systems 30, 2017	967	2017
Large batch optimization for deep learning: Training bert in 76 minutes Y You, J Li, S Reddi, J Hseu, S Kumar, S Bhojanapalli, X Song, J Demmel, ... arXiv preprint arXiv:1904.00962, 2019	543	2019
A pac-bayesian approach to spectrally-normalized margin bounds for neural networks B Neyshabur, S Bhojanapalli, N Srebro arXiv preprint arXiv:1707.09564, 2017	482	2017
Towards understanding the role of over-parametrization in generalization of neural networks B Neyshabur, Z Li, S Bhojanapalli, Y LeCun, N Srebro arXiv preprint arXiv:1805.12076, 2018	453	2018
Global optimality of local search for low rank matrix recovery S Bhojanapalli, B Neyshabur, N Srebro Advances in Neural Information Processing Systems, 3873-3881, 2016	373	2016
Implicit regularization in matrix factorization S Gunasekar, BE Woodworth, S Bhojanapalli, B Neyshabur, N Srebro Advances in Neural Information Processing Systems 30, 2017	329	2017
Dropping convexity for faster semi-definite optimization S Bhojanapalli, A Kyrillidis, S Sanghavi Conference on Learning Theory, 530-582, 2016	173	2016
Does label smoothing mitigate label noise? M Lukasik, S Bhojanapalli, A Menon, S Kumar International Conference on Machine Learning, 6448-6458, 2020	171	2020
Understanding robustness of transformers for image classification S Bhojanapalli, A Chakrabarti, D Glasner, D Li, T Unterthiner, A Veit Proceedings of the IEEE/CVF international conference on computer vision …, 2021	154	2021
Coherent matrix completion. Y Chen, S Bhojanapalli, S Sanghavi, R Ward arXiv preprint arXiv:1306.2979, 2013	139	2013
Are transformers universal approximators of sequence-to-sequence functions? C Yun, S Bhojanapalli, AS Rawat, SJ Reddi, S Kumar arXiv preprint arXiv:1912.10077, 2019	115	2019
Universal matrix completion S Bhojanapalli, P Jain International Conference on Machine Learning, 1881-1889, 2014	105	2014
Stabilizing GAN training with multiple random projections B Neyshabur, S Bhojanapalli, A Chakrabarti arXiv preprint arXiv:1705.07831, 2017	83	2017
Completing any low-rank matrix, provably Y Chen, S Bhojanapalli, S Sanghavi, R Ward The Journal of Machine Learning Research 16 (1), 2999-3034, 2015	78	2015
Tighter low-rank approximation via sampling the leveraged element S Bhojanapalli, P Jain, S Sanghavi Proceedings of the twenty-sixth annual ACM-SIAM symposium on Discrete …, 2014	41	2014
Low-rank bottleneck in multi-head attention models S Bhojanapalli, C Yun, AS Rawat, S Reddi, S Kumar International Conference on Machine Learning, 864-873, 2020	37	2020
Smoothed analysis for low-rank solutions to semidefinite programs in quadratic penalty form S Bhojanapalli, N Boumal, P Jain, P Netrapalli Conference On Learning Theory, 3243-3270, 2018	35	2018
A new sampling technique for tensors S Bhojanapalli, S Sanghavi arXiv preprint arXiv:1502.05023, 2015	34	2015
O (n) connections are expressive enough: Universal approximability of sparse transformers C Yun, YW Chang, S Bhojanapalli, AS Rawat, S Reddi, S Kumar Advances in Neural Information Processing Systems 33, 13783-13794, 2020	29	2020
Coping with label shift via distributionally robust optimisation J Zhang, A Menon, A Veit, S Bhojanapalli, S Kumar, S Sra arXiv preprint arXiv:2010.12230, 2020	27	2020

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