| Stability is stable: Connections between replicability, privacy, and adaptive generalization M Bun, M Gaboardi, M Hopkins, R Impagliazzo, R Lei, T Pitassi, ... Proceedings of the 55th Annual ACM Symposium on Theory of Computing, 520-527, 2023 | 42* | 2023 |
| Realizable learning is all you need M Hopkins, DM Kane, S Lovett, G Mahajan Conference on Learning Theory, 3015-3069, 2022 | 32 | 2022 |
| Noise-tolerant, reliable active classification with comparison queries M Hopkins, D Kane, S Lovett, G Mahajan Conference on Learning Theory, 1957-2006, 2020 | 29 | 2020 |
| High dimensional expanders: Eigenstripping, pseudorandomness, and unique games M Bafna, M Hopkins, T Kaufman, S Lovett Proceedings of the 2022 Annual ACM-SIAM Symposium on Discrete Algorithms …, 2022 | 28* | 2022 |
| Explicit lower bounds against ω (n)-rounds of sum-of-squares M Hopkins, TC Lin 2022 IEEE 63rd Annual Symposium on Foundations of Computer Science (FOCS …, 2022 | 27* | 2022 |
| Hypercontractivity on high dimensional expanders M Bafna, M Hopkins, T Kaufman, S Lovett Proceedings of the 54th Annual ACM SIGACT Symposium on Theory of Computing …, 2022 | 24* | 2022 |
| The power of comparisons for actively learning linear classifiers M Hopkins, D Kane, S Lovett Advances in Neural Information Processing Systems 33, 6342-6353, 2020 | 24 | 2020 |
| Point location and active learning: Learning halfspaces almost optimally M Hopkins, D Kane, S Lovett, G Mahajan 2020 IEEE 61st Annual Symposium on Foundations of Computer Science (FOCS …, 2020 | 22 | 2020 |
| Simulated annealing for jpeg quantization M Hopkins, M Mitzenmacher, S Wagner-Carena arXiv preprint arXiv:1709.00649, 2017 | 21 | 2017 |
| Robust empirical risk minimization with tolerance R Bhattacharjee, M Hopkins, A Kumar, H Yu, K Chaudhuri International Conference on Algorithmic Learning Theory, 182-203, 2023 | 11 | 2023 |
| Sampling equilibria: Fast no-regret learning in structured games D Beaglehole, M Hopkins, D Kane, S Liu, S Lovett Proceedings of the 2023 Annual ACM-SIAM Symposium on Discrete Algorithms …, 2023 | 10 | 2023 |
| A novel CMB component separation method: hierarchical generalized morphological component analysis S Wagner-Carena, M Hopkins, A Diaz Rivero, C Dvorkin Monthly Notices of the Royal Astronomical Society 494 (1), 1507-1529, 2020 | 10 | 2020 |
| Doppelgangers: the Ur-operation and posets of bounded height T Browning, M Hopkins, Z Kelley arXiv preprint arXiv:1710.10407, 2017 | 10* | 2017 |
| Eigenstripping, Spectral Decay, and Edge-Expansion on Posets J Gaitonde, M Hopkins, T Kaufman, S Lovett, R Zhang arXiv preprint arXiv:2205.00644, 2022 | 9* | 2022 |
| Bounded memory active learning through enriched queries M Hopkins, D Kane, S Lovett, M Moshkovitz Conference on Learning Theory, 2358-2387, 2021 | 8 | 2021 |
| Replicability in high dimensional statistics M Hopkins, R Impagliazzo, D Kane, S Liu, C Ye 2024 IEEE 65th Annual Symposium on Foundations of Computer Science (FOCS), 1-8, 2024 | 6* | 2024 |
| Active learning polynomial threshold functions O Ben-Eliezer, M Hopkins, C Yang, H Yu Advances in Neural Information Processing Systems 35, 24199-24212, 2022 | 6 | 2022 |
| Chernoff bounds and reverse hypercontractivity on hdx Y Dikstein, M Hopkins 2024 IEEE 65th Annual Symposium on Foundations of Computer Science (FOCS …, 2024 | 5 | 2024 |
| Do PAC-Learners Learn the Marginal Distribution? M Hopkins, DM Kane, S Lovett, G Mahajan arXiv preprint arXiv:2302.06285, 2023 | 5 | 2023 |
| Representation-theoretic techniques for independence bounds of Cayley graphs M Hopkins Bachelor thesis, 2018 | 3 | 2018 |
Shachar LovettFull Professor of Computer Science, University of California San DiegoVerified email at eng.ucsd.edu