| 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 | 106 | 2020 |
| Post-processing for individual fairness F Petersen, D Mukherjee, Y Sun, M Yurochkin Advances in Neural Information Processing Systems 34, 25944-25955, 2021 | 87 | 2021 |
| Outlier-robust optimal transport D Mukherjee, A Guha, JM Solomon, Y Sun, M Yurochkin International Conference on Machine Learning, 7850-7860, 2021 | 61 | 2021 |
| Does enforcing fairness mitigate biases caused by subpopulation shift? S Maity, D Mukherjee, M Yurochkin, Y Sun Advances in Neural Information Processing Systems 34, 25773-25784, 2021 | 25 | 2021 |
| Domain adaptation meets individual fairness. and they get along. D Mukherjee, F Petersen, M Yurochkin, Y Sun Advances in Neural Information Processing Systems 35, 28902-28913, 2022 | 21 | 2022 |
| Optimal linear discriminators for the discrete choice model in growing dimensions D Mukherjee, M Banerjee, Y Ritov The Annals of Statistics 49 (6), 3324-3357, 2021 | 12* | 2021 |
| There is no trade-off: enforcing fairness can improve accuracy S Maity, D Mukherjee, M Yurochkin, Y Sun stat 1050, 6, 2020 | 11 | 2020 |
| Markovian and non-Markovian processes with active decision making strategies For addressing the COVID-19 pandemic H Eftekhari, D Mukherjee, M Banerjee, Y Ritov arXiv preprint arXiv:2008.00375, 2020 | 8 | 2020 |
| Asymptotic normality of a change plane estimator in fixed dimension with near-optimal rate D Mukherjee, M Banerjee, D Mukherjee, Y Ritov Electronic Journal of Statistics 17 (2), 2289-2316, 2023 | 7* | 2023 |
| Predictor-corrector algorithms for stochastic optimization under gradual distribution shift S Maity, D Mukherjee, M Banerjee, Y Sun arXiv preprint arXiv:2205.13575, 2022 | 5 | 2022 |
| UTOPIA: Universally Trainable Optimal Prediction Intervals Aggregation J Fan, J Ge, D Mukherjee arXiv preprint arXiv:2306.16549, 2023 | 4 | 2023 |
| Deep neural networks for nonparametric interaction models with diverging dimension S Bhattacharya, J Fan, D Mukherjee arXiv preprint arXiv:2302.05851, 2023 | 4 | 2023 |
| On robust learning in the canonical change point problem under heavy tailed errors in finite and growing dimensions D Mukherjee, M Banerjee, Y Ritov Electronic Journal of Statistics 16 (1), 1153-1252, 2022 | 4 | 2022 |
| Trade-off Between Dependence and Complexity for Nonparametric Learning--an Empirical Process Approach N Deb, D Mukherjee arXiv preprint arXiv:2401.08978, 2024 | 2 | 2024 |
| Learning Mahalanobis Distance Metrics from Data M Yurochkin, D Mukherjee, M Banerjee, Y Sun, S Upadhyay US Patent App. 17/345,730, 2022 | 1 | 2022 |
| Estimation of a score-explained non-randomized treatment effect in fixed and high dimensions D Mukherjee, M Banerjee, Y Ritov arXiv preprint arXiv:2102.11229, 2021 | 1 | 2021 |
| On the estimation rate of Bayesian PINN for inverse problems Y Sun, D Mukherjee, Y Atchade arXiv preprint arXiv:2406.14808, 2024 | | 2024 |
| Transfer Learning Under High-Dimensional Graph Convolutional Regression Model for Node Classification J Chen, D Huang, L Wang, KL Lunetta, D Mukherjee, H Cheng arXiv preprint arXiv:2405.16672, 2024 | | 2024 |
| Optimal Aggregation of Prediction Intervals under Unsupervised Domain Shift J Ge, D Mukherjee, J Fan arXiv preprint arXiv:2405.10302, 2024 | | 2024 |
| Minimax Optimal rates of convergence in the shuffled regression, unlinked regression, and deconvolution under vanishing noise C Durot, D Mukherjee arXiv preprint arXiv:2404.09306, 2024 | | 2024 |
Yuekai SunUniversity of MichiganPotvrđena adresa e-pošte na umich.edu
