| Learnability can be undecidable S Ben-David, P Hrubeš, S Moran, A Shpilka, A Yehudayoff Nature Machine Intelligence 1 (1), 44-48, 2019 | 117* | 2019 |
| Private PAC learning implies finite Littlestone dimension N Alon, R Livni, M Malliaris, S Moran Proceedings of the 51st Annual ACM SIGACT Symposium on Theory of Computing …, 2019 | 114 | 2019 |
| Learners that use little information R Bassily, S Moran, I Nachum, J Shafer, A Yehudayoff Algorithmic Learning Theory, 25-55, 2018 | 108 | 2018 |
| Sample compression schemes for VC classes S Moran, A Yehudayoff Journal of the ACM (JACM) 63 (3), 1-10, 2016 | 95 | 2016 |
| An equivalence between private classification and online prediction M Bun, R Livni, S Moran 2020 IEEE 61st Annual Symposium on Foundations of Computer Science (FOCS …, 2020 | 77 | 2020 |
| Sign rank versus Vapnik-Chervonenkis dimension N Alon, S Moran, A Yehudayoff Sbornik: Mathematics 208 (12), 1724, 2017 | 76* | 2017 |
| Active classification with comparison queries DM Kane, S Lovett, S Moran, J Zhang 2017 IEEE 58th Annual Symposium on Foundations of Computer Science (FOCS …, 2017 | 72 | 2017 |
| Limits of private learning with access to public data N Alon, R Bassily, S Moran Advances in neural information processing systems 32, 2019 | 61 | 2019 |
| On statistical learning via the lens of compression O David, S Moran, A Yehudayoff arXiv preprint arXiv:1610.03592, 2016 | 60* | 2016 |
| Private query release assisted by public data R Bassily, A Cheu, S Moran, A Nikolov, J Ullman, S Wu International Conference on Machine Learning, 695-703, 2020 | 56 | 2020 |
| Adversarial laws of large numbers and optimal regret in online classification N Alon, O Ben-Eliezer, Y Dagan, S Moran, M Naor, E Yogev Proceedings of the 53rd annual ACM SIGACT symposium on theory of computing …, 2021 | 50 | 2021 |
| Proper learning, Helly number, and an optimal SVM bound O Bousquet, S Hanneke, S Moran, N Zhivotovskiy Conference on Learning Theory, 582-609, 2020 | 47 | 2020 |
| Near-optimal linear decision trees for k-SUM and related problems DM Kane, S Lovett, S Moran Journal of the ACM (JACM) 66 (3), 1-18, 2019 | 47 | 2019 |
| A theory of universal learning O Bousquet, S Hanneke, S Moran, R Van Handel, A Yehudayoff Proceedings of the 53rd Annual ACM SIGACT Symposium on Theory of Computing …, 2021 | 44 | 2021 |
| Teaching and compressing for low VC-dimension S Moran, A Shpilka, A Wigderson, A Yehudayoff A Journey Through Discrete Mathematics: A Tribute to Jiří Matoušek, 633-656, 2017 | 37* | 2017 |
| A theory of PAC learnability of partial concept classes N Alon, S Hanneke, R Holzman, S Moran 2021 IEEE 62nd Annual Symposium on Foundations of Computer Science (FOCS …, 2022 | 36 | 2022 |
| Towards a unified information-theoretic framework for generalization M Haghifam, GK Dziugaite, S Moran, D Roy Advances in Neural Information Processing Systems 34, 26370-26381, 2021 | 35 | 2021 |
| Private center points and learning of halfspaces A Beimel, S Moran, K Nissim, U Stemmer Conference on Learning Theory, 269-282, 2019 | 34 | 2019 |
| A characterization of multiclass learnability N Brukhim, D Carmon, I Dinur, S Moran, A Yehudayoff 2022 IEEE 63rd Annual Symposium on Foundations of Computer Science (FOCS …, 2022 | 32 | 2022 |
| A limitation of the PAC-Bayes framework R Livni, S Moran Advances in Neural Information Processing Systems 33, 20543-20553, 2020 | 32 | 2020 |
Amir YehudayoffDIKU, University of Copenhagen, and Department of Mathematics, Technion在 technion.ac.il 的电子邮件经过验证
