Srinadh Bhojanapalli

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Behnam NeyshaburSenior Staff Research Scientist, DeepMindVerified email at google.com
Nathan SrebroProfessor, TTIC and University of ChicagoVerified email at ttic.edu
Sujay SanghaviAssociate Professor, Electrical and Computer Engineering, University of Texas, AustinVerified email at mail.utexas.edu
Prateek JainGoogle Research IndiaVerified email at google.com
Ayan ChakrabartiGoogle ResearchVerified email at google.com
Anastasios KyrillidisAssociate Professor, Computer Science Department, Ken Kennedy Institute Fellow, Rice UniversityVerified email at rice.edu
Rachel WardVerified email at math.utexas.edu
Yudong ChenAssociate Professor, University of Wisconsin-MadisonVerified email at wisc.edu
Zhiyuan LiAssistant Professor, Toyota Technological Institute at ChicagoVerified email at ttic.edu
Yann LeCunChief AI Scientist at Facebook & Silver Professor at the Courant Institute, New York UniversityVerified email at cs.nyu.edu
Constantine CaramanisProfessor of Electrical and Computer Engineering, UT AustinVerified email at utexas.edu
Dohyung ParkThe University of Texas at AustinVerified email at utexas.edu
Praneeth NetrapalliGoogle ResearchVerified email at google.com
Amir KalevInformation Sciences Institute, University of Southern CaliforniaVerified email at isi.edu
Nicolas BoumalEcole Polytechnique Fédérale de Lausanne (EPFL)Verified email at epfl.ch
Alexandros G DimakisProfessor, ECE University of Texas at AustinVerified email at austin.utexas.edu
David McAllesterProfessor, Toyota Technological Institute at ChicagoVerified email at ttic.edu

Srinadh Bhojanapalli

Research Scientist, Google Research

Verified email at google.com - Homepage

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Exploring generalization in deep learning B Neyshabur, S Bhojanapalli, D McAllester, N Srebro Advances in neural information processing systems 30, 2017	1393	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	995	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	660	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	598	2018
Implicit regularization in matrix factorization S Gunasekar, BE Woodworth, S Bhojanapalli, B Neyshabur, N Srebro Advances in neural information processing systems 30, 2017	531	2017
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	442	2016
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	416	2021
Does label smoothing mitigate label noise? M Lukasik, S Bhojanapalli, A Menon, S Kumar International Conference on Machine Learning, 6448-6458, 2020	371	2020
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	325	2019
Dropping convexity for faster semi-definite optimization S Bhojanapalli, A Kyrillidis, S Sanghavi Conference on Learning Theory, 530-582, 2016	183	2016
Coherent matrix completion. Y Chen, S Bhojanapalli, S Sanghavi, R Ward arXiv preprint arXiv:1306.2979, 2013	147	2013
Modifying memories in transformer models C Zhu, AS Rawat, M Zaheer, S Bhojanapalli, D Li, F Yu, S Kumar arXiv preprint arXiv:2012.00363, 2020	128	2020
Universal matrix completion S Bhojanapalli, P Jain International Conference on Machine Learning, 1881-1889, 2014	127	2014
Stabilizing GAN training with multiple random projections B Neyshabur, S Bhojanapalli, A Chakrabarti arXiv preprint arXiv:1705.07831, 2017	106	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	95	2015
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	80	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	71	2020
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	68	2020
The lazy neuron phenomenon: On emergence of activation sparsity in transformers Z Li, C You, S Bhojanapalli, D Li, AS Rawat, SJ Reddi, K Ye, F Chern, ... arXiv preprint arXiv:2210.06313, 2022	59	2022
A simple and effective positional encoding for transformers PC Chen, H Tsai, S Bhojanapalli, HW Chung, YW Chang, CS Ferng arXiv preprint arXiv:2104.08698, 2021	56	2021

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