| Strongly adaptive online learning A Daniely, A Gonen, S Shalev-Shwartz International Conference on Machine Learning, 1405-1411, 2015 | 187 | 2015 |
| Large-scale convex minimization with a low-rank constraint S Shalev-Shwartz, A Gonen, O Shamir arXiv preprint arXiv:1106.1622, 2011 | 173 | 2011 |
| Learning in non-convex games with an optimization oracle N Agarwal, A Gonen, E Hazan Conference on Learning Theory, 18-29, 2019 | 58 | 2019 |
| Efficient active learning of halfspaces: an aggressive approach A Gonen, S Sabato, S Shalev-Shwartz International Conference on Machine Learning, 480-488, 2013 | 54* | 2013 |
| Solving ridge regression using sketched preconditioned svrg A Gonen, F Orabona, S Shalev-Shwartz International conference on machine learning, 1397-1405, 2016 | 50 | 2016 |
| The sample complexity of subspace learning with partial information A Gonen, D Rosenbaum, Y Eldar, S Shalev-Shwartz The Journal of Machine Learning Research 17, 1821--1841, 2014 | 46* | 2014 |
| Fast rates for empirical risk minimization of strict saddle problems A Gonen, S Shalev-Shwartz Proceedings of the 30th Conference on Learning Theory, 1043-1063, 2017 | 33 | 2017 |
| Average stability is invariant to data preconditioning. implications to exp-concave empirical risk minimization A Gonen, S Shalev-Shwartz Journal of Machine Learning Research 18, 222:1--222:13, 2018 | 29* | 2018 |
| Private learning implies online learning: An efficient reduction A Gonen, E Hazan, S Moran Advances in Neural Information Processing Systems 32, 2019 | 22 | 2019 |
| Boosting simple learners N Alon, A Gonen, E Hazan, S Moran Proceedings of the 53rd Annual ACM SIGACT Symposium on Theory of Computing …, 2021 | 18 | 2021 |
| Faster sgd using sketched conditioning A Gonen, S Shalev-Shwartz arXiv preprint arXiv:1506.02649, 2015 | 16 | 2015 |
| Towards a combinatorial characterization of bounded-memory learning A Gonen, S Lovett, M Moshkovitz Advances in Neural Information Processing Systems 33, 9028-9038, 2020 | 15 | 2020 |
| Learning in non-convex games with an optimization oracle A Gonen, E Hazan arXiv preprint arXiv:1810.07362, 78, 2018 | 9 | 2018 |
| Smooth sensitivity based approach for differentially private principal component analysis A Gonen, R Gilad-Bachrach arXiv preprint arXiv:1710.10556, 2017 | 5 | 2017 |
| Smooth sensitivity based approach for differentially private principal component analysis R Gilad-Bachrach, A Gonen arXiv preprint arXiv:1710.10556, 2017 | 1 | 2017 |
| Learning Perturbation-specific Cell Representations for Prediction of Transcriptional Response across Cellular Contexts G Keinan, K Sayal, A Gonen, J Zhu, L Granovsky, J England bioRxiv, 2023.03. 20.533433, 2023 | | 2023 |
| Optimal Sketching Bounds for Exp-concave Stochastic Minimization N Agarwal, A Gonen arXiv preprint arXiv:1805.08268, 2018 | | 2018 |
| Effective Dimension of Exp-concave Optimization N Agarwal, A Gonen arXiv preprint arXiv:1805.08268, 2018 | | 2018 |
Shai Shalev-ShwartzThe Hebrew UniversityVerified email at cs.huji.ac.il
