| Federated learning with matched averaging H Wang, M Yurochkin, Y Sun, D Papailiopoulos, Y Khazaeni arXiv preprint arXiv:2002.06440, 2020 | 1758 | 2020 |
| Creation and analysis of biochemical constraint-based models using the COBRA Toolbox v. 3.0 L Heirendt, S Arreckx, T Pfau, SN Mendoza, A Richelle, A Heinken, ... Nature protocols 14 (3), 639-702, 2019 | 1392 | 2019 |
| Exact post-selection inference, with application to the lasso JD Lee, DL Sun, Y Sun, JE Taylor | 1083 | 2016 |
| Proximal Newton-type methods for minimizing composite functions JD Lee, Y Sun, MA Saunders SIAM Journal on Optimization 24 (3), 1420-1443, 2014 | 413 | 2014 |
| Communication-efficient sparse regression JD Lee, Q Liu, Y Sun, JE Taylor The Journal of Machine Learning Research 18 (1), 115-144, 2017 | 289 | 2017 |
| Nanostructure on taro leaves resists fouling by colloids and bacteria under submerged conditions J Ma, Y Sun, K Gleichauf, J Lou, Q Li Langmuir 27 (16), 10035-10040, 2011 | 200 | 2011 |
| Training individually fair ML models with sensitive subspace robustness M Yurochkin, A Bower, Y Sun arXiv preprint arXiv:1907.00020, 2019 | 164 | 2019 |
| Two simple ways to learn individual fairness metrics from data D Mukherjee, M Yurochkin, M Banerjee, Y Sun International conference on machine learning, 7097-7107, 2020 | 150 | 2020 |
| Post-processing for individual fairness F Petersen, D Mukherjee, Y Sun, M Yurochkin Advances in Neural Information Processing Systems 34, 25944-25955, 2021 | 149 | 2021 |
| Proximal Newton-type methods for convex optimization JD Lee, Y Sun, M Saunders Advances in Neural Information Processing Systems 25, 2012 | 135 | 2012 |
| Large language model routing with benchmark datasets T Shnitzer, A Ou, M Silva, K Soule, Y Sun, J Solomon, N Thompson, ... arXiv preprint arXiv:2309.15789, 2023 | 129 | 2023 |
| Outlier-robust optimal transport D Mukherjee, A Guha, JM Solomon, Y Sun, M Yurochkin International Conference on Machine Learning, 7850-7860, 2021 | 90 | 2021 |
| tinyBenchmarks: evaluating LLMs with fewer examples FM Polo, L Weber, L Choshen, Y Sun, G Xu, M Yurochkin arXiv preprint arXiv:2402.14992, 2024 | 81 | 2024 |
| Statistical convergence of the EM algorithm on Gaussian mixture models R Zhao, Y Li, Y Sun | 79 | 2020 |
| Sensei: Sensitive set invariance for enforcing individual fairness M Yurochkin, Y Sun arXiv preprint arXiv:2006.14168, 2020 | 77 | 2020 |
| Fusing models with complementary expertise H Wang, FM Polo, Y Sun, S Kundu, E Xing, M Yurochkin arXiv preprint arXiv:2310.01542, 2023 | 76 | 2023 |
| On model selection consistency of regularized M-estimators JD Lee, Y Sun, JE Taylor | 73 | 2015 |
| Communication-efficient sparse regression: a one-shot approach JD Lee, Y Sun, Q Liu, JE Taylor arXiv preprint arXiv:1503.04337, 2015 | 71 | 2015 |
| Do genome‐scale models need exact solvers or clearer standards? A Ebrahim, E Almaas, E Bauer, A Bordbar, AP Burgard, RL Chang, ... Molecular systems biology 11 (10), 831, 2015 | 69 | 2015 |
| Selective degradation of hemicellulose and lignin for improving enzymolysis efficiency via pretreatment using deep eutectic solvents D Huo, Y Sun, Q Yang, F Zhang, G Fang, H Zhu, Y Liu Bioresource Technology 376, 128937, 2023 | 66 | 2023 |
Mikhail YurochkinStaff AI Scientist, IFM MBZUAI, ex MIT-IBM Watson AI LabVerified email at umich.edu
