| On the convergence of adam and beyond SJ Reddi, S Kale, S Kumar arXiv preprint arXiv:1904.09237, 2019 | 3206 | 2019 |
| Adaptive federated optimization S Reddi, Z Charles, M Zaheer, Z Garrett, K Rush, J Konečný, S Kumar, ... arXiv preprint arXiv:2003.00295, 2020 | 1519 | 2020 |
| Hashing with graphs W Liu, J Wang, S Kumar, SF Chang Proceedings of the 28th international conference on machine learning (ICML …, 2011 | 1224 | 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 | 1061 | 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 | 948 | 2012 |
| Long-tail learning via logit adjustment AK Menon, S Jayasumana, AS Rawat, H Jain, A Veit, S Kumar arXiv preprint arXiv:2007.07314, 2020 | 774 | 2020 |
| Semi-supervised hashing for scalable image retrieval J Wang, S Kumar, SF Chang 2010 IEEE Computer Society Conference on Computer Vision and Pattern …, 2010 | 746 | 2010 |
| Discriminative random fields: A discriminative framework for contextual interaction in classification S Kumar Proceedings ninth IEEE international conference on computer vision, 1150-1157, 2003 | 651 | 2003 |
| Discrete graph hashing W Liu, C Mu, S Kumar, SF Chang Advances in neural information processing systems 27, 2014 | 637 | 2014 |
| 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 | 633 | 2015 |
| 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 | 627 | 2008 |
| A new baseline for image annotation A Makadia, V Pavlovic, S Kumar Computer Vision–ECCV 2008: 10th European Conference on Computer Vision …, 2008 | 614 | 2008 |
| 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 | 543 | 2018 |
| Discriminative random fields S Kumar, M Hebert International Journal of Computer Vision 68, 179-201, 2006 | 524 | 2006 |
| Adaptive methods for nonconvex optimization M Zaheer, S Reddi, D Sachan, S Kale, S Kumar Advances in neural information processing systems 31, 2018 | 513 | 2018 |
| Sampling methods for the Nyström method S Kumar, M Mohri, A Talwalkar The Journal of Machine Learning Research 13 (1), 981-1006, 2012 | 476 | 2012 |
| 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 | 432 | 2020 |
| Efficient natural language response suggestion for smart reply M Henderson, R Al-Rfou, B Strope, YH Sung, L Lukács, R Guo, S Kumar, ... arXiv preprint arXiv:1705.00652, 2017 | 404 | 2017 |
| 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 | 401 | 2015 |
| Distributed mean estimation with limited communication AT Suresh, XY Felix, S Kumar, HB McMahan International conference on machine learning, 3329-3337, 2017 | 396 | 2017 |
Sashank J. ReddiResearch Scientist, Google Research在 cs.cmu.edu 的电子邮件经过验证
