Srinadh Bhojanapalli
Srinadh Bhojanapalli
Research Scientist, Google Research
Verified email at google.com - Homepage
Title
Cited by
Cited by
Year
Exploring generalization in deep learning
B Neyshabur, S Bhojanapalli, D McAllester, N Srebro
Advances in neural information processing systems, 5947-5956, 2017
3602017
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
2512016
A pac-bayesian approach to spectrally-normalized margin bounds for neural networks
B Neyshabur, S Bhojanapalli, N Srebro
arXiv preprint arXiv:1707.09564, 2017
2082017
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
155*2018
Implicit regularization in matrix factorization
S Gunasekar, BE Woodworth, S Bhojanapalli, B Neyshabur, N Srebro
Advances in Neural Information Processing Systems, 6151-6159, 2017
1222017
Dropping convexity for faster semi-definite optimization
S Bhojanapalli, A Kyrillidis, S Sanghavi
Conference on Learning Theory, 530-582, 2016
1192016
Coherent matrix completion.
Y Chen, S Bhojanapalli, S Sanghavi, R Ward
arXiv preprint arXiv:1306.2979, 2013
1162013
Universal matrix completion
S Bhojanapalli, P Jain
arXiv preprint arXiv:1402.2324, 2014
802014
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
492019
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
442015
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
392014
A new sampling technique for tensors
S Bhojanapalli, S Sanghavi
arXiv preprint arXiv:1502.05023, 2015
302015
Stabilizing GAN training with multiple random projections
B Neyshabur, S Bhojanapalli, A Chakrabarti
arXiv preprint arXiv:1705.07831, 2017
282017
Completing any low-rank matrix, provably
Y Chen, S Bhojanapalli, S Sanghavi, R Ward
arXiv preprint arXiv:1306.2979, 2013
272013
Smoothed analysis for low-rank solutions to semidefinite programs in quadratic penalty form
S Bhojanapalli, N Boumal, P Jain, P Netrapalli
arXiv preprint arXiv:1803.00186, 2018
222018
Provable Burer-Monteiro factorization for a class of norm-constrained matrix problems
D Park, A Kyrillidis, S Bhojanapalli, C Caramanis, S Sanghavi
arXiv preprint arXiv:1606.01316, 2016
222016
Provable non-convex projected gradient descent for a class of constrained matrix optimization problems
D Park, A Kyrillidis, S Bhojanapalli, C Caramanis, S Sanghavi
stat 1050, 4, 2016
182016
Single pass PCA of matrix products
S Wu, S Bhojanapalli, S Sanghavi, AG Dimakis
Advances in Neural Information Processing Systems, 2585-2593, 2016
82016
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
62019
Provable compressed sensing quantum state tomography via non-convex methods
A Kyrillidis, A Kalev, D Park, S Bhojanapalli, C Caramanis, S Sanghavi
npj Quantum Information 4 (1), 1-7, 2018
52018
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