| Turning Big Data Into Tiny Data: Constant-Size Coresets for -Means, PCA, and Projective Clustering D Feldman, M Schmidt, C Sohler SIAM Journal on Computing 49 (3), 601-657, 2020 | 672 | 2020 |
| A unified framework for approximating and clustering data D Feldman, M Langberg Proceedings of the forty-third annual ACM symposium on Theory of computing …, 2011 | 525 | 2011 |
| A PTAS for k-means clustering based on weak coresets D Feldman, M Monemizadeh, C Sohler Proceedings of the twenty-third annual symposium on Computational geometry …, 2007 | 230 | 2007 |
| Provable filter pruning for efficient neural networks L Liebenwein, C Baykal, H Lang, D Feldman, D Rus arXiv preprint arXiv:1911.07412, 2019 | 195 | 2019 |
| Scalable training of mixture models via coresets D Feldman, M Faulkner, A Krause Advances in neural information processing systems 24, 2011 | 186 | 2011 |
| New frameworks for offline and streaming coreset constructions V Braverman, D Feldman, H Lang, A Statman, S Zhou arXiv preprint arXiv:1612.00889, 2016 | 175 | 2016 |
| The solution for data analysis and presentation graphics D Feldman, J Ganon, R Haffman, J Simpson Abacus Lancripts, Inc., Berkeley, USA, 2003 | 175 | 2003 |
| Private coresets D Feldman, A Fiat, H Kaplan, K Nissim Proceedings of the forty-first annual ACM symposium on Theory of computing …, 2009 | 168 | 2009 |
| Training gaussian mixture models at scale via coresets M Lucic, M Faulkner, A Krause, D Feldman Journal of Machine Learning Research 18 (160), 1-25, 2018 | 154 | 2018 |
| Coresets and sketches for high dimensional subspace approximation problems D Feldman, M Monemizadeh, C Sohler, DP Woodruff Proceedings of the twenty-first annual ACM-SIAM symposium on Discrete …, 2010 | 119 | 2010 |
| Core-sets: Updated survey D Feldman Sampling techniques for supervised or unsupervised tasks, 23-44, 2020 | 111 | 2020 |
| StatView II: the solution for data analysis and presentation graphics DS Feldman Jr, J Gagnon, R Hofman, J Simpson Abacus Concepts, Berkeley, 1987 | 107 | 1987 |
| Data-dependent coresets for compressing neural networks with applications to generalization bounds C Baykal, L Liebenwein, I Gilitschenski, D Feldman, D Rus arXiv preprint arXiv:1804.05345, 2018 | 95 | 2018 |
| Trajectory clustering for motion prediction C Sung, D Feldman, D Rus 2012 IEEE/RSJ International Conference on Intelligent Robots and Systems …, 2012 | 88 | 2012 |
| Data reduction for weighted and outlier-resistant clustering D Feldman, LJ Schulman Proceedings of the twenty-third annual ACM-SIAM symposium on Discrete …, 2012 | 86 | 2012 |
| Introduction to core-sets: an updated survey D Feldman arXiv preprint arXiv:2011.09384, 2020 | 75 | 2020 |
| Fast and accurate least-mean-squares solvers A Maalouf, I Jubran, D Feldman Advances in Neural Information Processing Systems 32, 2019 | 72 | 2019 |
| Dimensionality reduction of massive sparse datasets using coresets D Feldman, M Volkov, D Rus Advances in neural information processing systems 29, 2016 | 71 | 2016 |
| Data-independent neural pruning via coresets B Mussay, M Osadchy, V Braverman, S Zhou, D Feldman arXiv preprint arXiv:1907.04018, 2019 | 68 | 2019 |
| Coresets for differentially private k-means clustering and applications to privacy in mobile sensor networks D Feldman, C Xiang, R Zhu, D Rus Proceedings of the 16th ACM/IEEE International Conference on Information …, 2017 | 67 | 2017 |
Daniela RusAndrew (1956) and Erna Viterbi Professor of Computer Science, MITcsail.mit.edu의 이메일 확인됨
