| Concentrated differential privacy: Simplifications, extensions, and lower bounds M Bun, T Steinke Theory of Cryptography Conference, 635-658, 2016 | 1039 | 2016 |
| Differential Privacy: A Primer for a Non-Technical Audience. A Wood, M Altman, A Bembenek, M Bun, M Gaboardi, J Honaker, ... Vanderbilt Journal of Entertainment & Technology Law 21 (1), 2018 | 347 | 2018 |
| Fingerprinting codes and the price of approximate differential privacy M Bun, J Ullman, S Vadhan SIAM Journal on Computing 47 (5), 1888-1938, 2018 | 257* | 2018 |
| Differentially private release and learning of threshold functions M Bun, K Nissim, U Stemmer, S Vadhan Foundations of Computer Science (FOCS), 2015 IEEE 56th Annual Symposium on …, 2015 | 224 | 2015 |
| Composable and versatile privacy via truncated CDP M Bun, C Dwork, GN Rothblum, T Steinke Proceedings of the 50th Annual ACM SIGACT Symposium on Theory of Computing …, 2018 | 205 | 2018 |
| Heavy Hitters and the Structure of Local Privacy M Bun, J Nelson, U Stemmer ACM Transactions on Algorithms (TALG) 15 (4), 51, 2019 | 184 | 2019 |
| Private hypothesis selection M Bun, G Kamath, T Steinke, ZS Wu IEEE Transactions on Information Theory, 2021 | 114 | 2021 |
| When is memorization of irrelevant training data necessary for high-accuracy learning? G Brown, M Bun, V Feldman, A Smith, K Talwar Proceedings of the 53rd Annual ACM SIGACT Symposium on Theory of Computing …, 2021 | 108 | 2021 |
| Simultaneous Private Learning of Multiple Concepts M Bun, K Nissim, U Stemmer Proceedings of the 2016 ACM Conference on Innovations in Theoretical …, 2016 | 102 | 2016 |
| Bridging the gap between computer science and legal approaches to privacy K Nissim, A Bembenek, A Wood, M Bun, M Gaboardi, U Gasser, D O’Brien, ... Harvard Journal of Law & Technology 31, 2017 | 100 | 2017 |
| New Oracle-Efficient Algorithms for Private Synthetic Data Release G Vietri, G Tian, M Bun, T Steinke, ZS Wu | 95* | |
| 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 | 91 | 2020 |
| Average-case averages: Private algorithms for smooth sensitivity and mean estimation M Bun, T Steinke Advances in Neural Information Processing Systems, 181-191, 2019 | 89 | 2019 |
| The polynomial method strikes back: Tight quantum query bounds via dual polynomials M Bun, R Kothari, J Thaler Proceedings of the 50th Annual ACM SIGACT Symposium on Theory of Computing …, 2018 | 81 | 2018 |
| Dual lower bounds for approximate degree and Markov–Bernstein inequalities M Bun, J Thaler Information and Computation 243, 2-25, 2015 | 69 | 2015 |
| Make up your mind: The price of online queries in differential privacy M Bun, T Steinke, J Ullman Proceedings of the Twenty-Eighth Annual ACM-SIAM Symposium on Discrete …, 2017 | 65 | 2017 |
| Differentially Private Submodular Maximization: Data Summarization in Disguise M Mitrovic, M Bun, A Krause, A Karbasi | 53* | |
| A Nearly Optimal Lower Bound on the Approximate Degree of AC^0 M Bun, J Thaler arXiv preprint arXiv:1703.05784, 2017 | 48 | 2017 |
| Hardness amplification and the approximate degree of constant-depth circuits M Bun, J Thaler International Colloquium on Automata, Languages, and Programming, 268-280, 2015 | 43 | 2015 |
| Private and online learnability are equivalent N Alon, M Bun, R Livni, M Malliaris, S Moran ACM Journal of the ACM (JACM) 69 (4), 1-34, 2022 | 36 | 2022 |