Sanjiv Kumar
Sanjiv Kumar
Google Fellow, VP, Google Research
Verified email at - Homepage
Cited by
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On the convergence of adam and beyond
SJ Reddi, S Kale, S Kumar
arXiv preprint arXiv:1904.09237, 2019
Adaptive federated optimization
S Reddi, Z Charles, M Zaheer, Z Garrett, K Rush, J Konečnı, S Kumar, ...
arXiv preprint arXiv:2003.00295, 2020
Hashing with graphs
W Liu, J Wang, S Kumar, SF Chang
Proceedings of the 28th international conference on machine learning (ICML …, 2011
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
Semi-supervised hashing for large-scale search
J Wang, S Kumar, SF Chang
IEEE transactions on pattern analysis and machine intelligence 34 (12), 2393 …, 2012
Semi-supervised hashing for scalable image retrieval
J Wang, S Kumar, SF Chang
2010 IEEE Computer Society Conference on Computer Vision and Pattern …, 2010
Long-tail learning via logit adjustment
AK Menon, S Jayasumana, AS Rawat, H Jain, A Veit, S Kumar
arXiv preprint arXiv:2007.07314, 2020
Discriminative random fields: A discriminative framework for contextual interaction in classification
S Kumar
Proceedings ninth IEEE international conference on computer vision, 1150-1157, 2003
Discrete graph hashing
W Liu, C Mu, S Kumar, SF Chang
Advances in neural information processing systems 27, 2014
Face tracking and recognition with visual constraints in real-world videos
M Kim, S Kumar, V Pavlovic, H Rowley
2008 IEEE Conference on computer vision and pattern recognition, 1-8, 2008
A new baseline for image annotation
A Makadia, V Pavlovic, S Kumar
Computer Vision–ECCV 2008: 10th European Conference on Computer Vision …, 2008
Learning to hash for indexing big data—A survey
J Wang, W Liu, S Kumar, SF Chang
Proceedings of the IEEE 104 (1), 34-57, 2015
Discriminative random fields
S Kumar, M Hebert
International Journal of Computer Vision 68, 179-201, 2006
cpSGD: Communication-efficient and differentially-private distributed SGD
N Agarwal, AT Suresh, FXX Yu, S Kumar, B McMahan
Advances in Neural Information Processing Systems 31, 2018
Adaptive methods for nonconvex optimization
M Zaheer, S Reddi, D Sachan, S Kale, S Kumar
Advances in neural information processing systems 31, 2018
Sampling methods for the Nyström method
S Kumar, M Mohri, A Talwalkar
The Journal of Machine Learning Research 13 (1), 981-1006, 2012
Sequential projection learning for hashing with compact codes
J Wang, S Kumar, SF Chang
An exploration of parameter redundancy in deep networks with circulant projections
Y Cheng, FX Yu, RS Feris, S Kumar, A Choudhary, SF Chang
Proceedings of the IEEE international conference on computer vision, 2857-2865, 2015
Distributed mean estimation with limited communication
AT Suresh, XY Felix, S Kumar, HB McMahan
International conference on machine learning, 3329-3337, 2017
Accelerating large-scale inference with anisotropic vector quantization
R Guo, P Sun, E Lindgren, Q Geng, D Simcha, F Chern, S Kumar
International Conference on Machine Learning, 3887-3896, 2020
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