| Robust estimators in high-dimensions without the computational intractability I Diakonikolas, G Kamath, D Kane, J Li, A Moitra, A Stewart SIAM Journal on Computing 48 (2), 742-864, 2019 | 526 | 2019 |
| Sever: A robust meta-algorithm for stochastic optimization I Diakonikolas, G Kamath, D Kane, J Li, J Steinhardt, A Stewart International Conference on Machine Learning, 1596-1606, 2019 | 328 | 2019 |
| Being robust (in high dimensions) can be practical I Diakonikolas, G Kamath, DM Kane, J Li, A Moitra, A Stewart International Conference on Machine Learning, 999-1008, 2017 | 270 | 2017 |
| Statistical query lower bounds for robust estimation of high-dimensional gaussians and gaussian mixtures I Diakonikolas, DM Kane, A Stewart 2017 IEEE 58th Annual Symposium on Foundations of Computer Science (FOCS), 73-84, 2017 | 256 | 2017 |
| Efficient algorithms and lower bounds for robust linear regression I Diakonikolas, W Kong, A Stewart Proceedings of the Thirtieth Annual ACM-SIAM Symposium on Discrete …, 2019 | 164 | 2019 |
| List-decodable robust mean estimation and learning mixtures of spherical gaussians I Diakonikolas, DM Kane, A Stewart Proceedings of the 50th Annual ACM SIGACT Symposium on Theory of Computing …, 2018 | 159 | 2018 |
| Robustly learning a gaussian: Getting optimal error, efficiently I Diakonikolas, G Kamath, DM Kane, J Li, A Moitra, A Stewart Proceedings of the Twenty-Ninth Annual ACM-SIAM Symposium on Discrete …, 2018 | 147 | 2018 |
| Overview of polkadot and its design considerations J Burdges, A Cevallos, P Czaban, R Habermeier, S Hosseini, F Lama, ... arXiv preprint arXiv:2005.13456, 2020 | 94 | 2020 |
| Testing bayesian networks CL Canonne, I Diakonikolas, DM Kane, A Stewart Conference on Learning Theory, 370-448, 2017 | 82 | 2017 |
| Learning geometric concepts with nasty noise I Diakonikolas, DM Kane, A Stewart Proceedings of the 50th Annual ACM SIGACT Symposium on Theory of Computing …, 2018 | 78 | 2018 |
| Robust learning of fixed-structure Bayesian networks Y Cheng, I Diakonikolas, D Kane, A Stewart Advances in Neural Information Processing Systems 31, 2018 | 59* | 2018 |
| Testing conditional independence of discrete distributions CL Canonne, I Diakonikolas, DM Kane, A Stewart Proceedings of the 50th Annual ACM SIGACT Symposium on Theory of Computing …, 2018 | 54 | 2018 |
| Grandpa: a byzantine finality gadget A Stewart, E Kokoris-Kogia arXiv preprint arXiv:2007.01560, 2020 | 53 | 2020 |
| A verifiably secure and proportional committee election rule A Cevallos, A Stewart Proceedings of the 3rd ACM Conference on Advances in Financial Technologies …, 2021 | 45 | 2021 |
| Outlier-robust high-dimensional sparse estimation via iterative filtering I Diakonikolas, D Kane, S Karmalkar, E Price, A Stewart Advances in Neural Information Processing Systems 32, 2019 | 45 | 2019 |
| The fourier transform of poisson multinomial distributions and its algorithmic applications I Diakonikolas, DM Kane, A Stewart Proceedings of the forty-eighth annual ACM symposium on Theory of Computing …, 2016 | 41 | 2016 |
| Optimal learning via the fourier transform for sums of independent integer random variables I Diakonikolas, DM Kane, A Stewart Conference on Learning Theory, 831-849, 2016 | 35 | 2016 |
| Efficient robust proper learning of log-concave distributions I Diakonikolas, DM Kane, A Stewart arXiv preprint arXiv:1606.03077, 2016 | 31 | 2016 |
| Polynomial time algorithms for multi-type branching processesand stochastic context-free grammars K Etessami, A Stewart, M Yannakakis Proceedings of the forty-fourth annual ACM symposium on Theory of computing …, 2012 | 29 | 2012 |
| Learning multivariate log-concave distributions I Diakonikolas, DM Kane, A Stewart Conference on Learning Theory, 711-727, 2017 | 28 | 2017 |
Ilias DiakonikolasUniversity of Wisconsin-MadisonVerified email at wisc.edu
