| Repairing without retraining: Avoiding disparate impact with counterfactual distributions H Wang, B Ustun, F Calmon International Conference on Machine Learning, 6618-6627, 2019 | 92* | 2019 |
| On the robustness of information-theoretic privacy measures and mechanisms M Diaz, H Wang, FP Calmon, L Sankar IEEE Transactions on Information Theory 66 (4), 1949-1978, 2019 | 55 | 2019 |
| An information-theoretic view of generalization via Wasserstein distance H Wang, M Diaz, JCS Santos Filho, FP Calmon 2019 IEEE International Symposium on Information Theory (ISIT), 577-581, 2019 | 53 | 2019 |
| An estimation-theoretic view of privacy H Wang, FP Calmon 2017 55th Annual Allerton Conference on Communication, Control, and …, 2017 | 41 | 2017 |
| Privacy with estimation guarantees H Wang, L Vo, FP Calmon, M Médard, KR Duffy, M Varia IEEE Transactions on Information Theory 65 (12), 8025-8042, 2019 | 40 | 2019 |
| Beyond adult and compas: Fair multi-class prediction via information projection W Alghamdi, H Hsu, H Jeong, H Wang, P Michalak, S Asoodeh, F Calmon Advances in Neural Information Processing Systems 35, 38747-38760, 2022 | 39* | 2022 |
| Analyzing the generalization capability of SGLD using properties of Gaussian channels H Wang, Y Huang, R Gao, F Calmon Advances in Neural Information Processing Systems 34, 24222-24234, 2021 | 34* | 2021 |
| Fairness without imputation: A decision tree approach for fair prediction with missing values H Jeong, H Wang, FP Calmon Proceedings of the AAAI Conference on Artificial Intelligence 36 (9), 9558-9566, 2022 | 33 | 2022 |
| To split or not to split: The impact of disparate treatment in classification H Wang, H Hsu, M Diaz, FP Calmon IEEE Transactions on Information Theory 67 (10), 6733-6757, 2021 | 32 | 2021 |
| Model projection: Theory and applications to fair machine learning W Alghamdi, S Asoodeh, H Wang, FP Calmon, D Wei, KN Ramamurthy 2020 IEEE International Symposium on Information Theory (ISIT), 2711-2716, 2020 | 21 | 2020 |
| The utility cost of robust privacy guarantees H Wang, M Diaz, FP Calmon, L Sankar 2018 IEEE International Symposium on Information Theory (ISIT), 706-710, 2018 | 17 | 2018 |
| Generalization bounds for noisy iterative algorithms using properties of additive noise channels H Wang, R Gao, FP Calmon Journal of machine learning research 24 (26), 1-43, 2023 | 15 | 2023 |
| On the direction of discrimination: An information-theoretic analysis of disparate impact in machine learning H Wang, B Ustun, FP Calmon 2018 IEEE International Symposium on Information Theory (ISIT), 126-130, 2018 | 10 | 2018 |
| Aleatoric and epistemic discrimination: Fundamental limits of fairness interventions H Wang, L He, R Gao, F Calmon Advances in Neural Information Processing Systems 36, 2024 | 9 | 2024 |
| Post-processing private synthetic data for improving utility on selected measures H Wang, S Sudalairaj, J Henning, K Greenewald, A Srivastava Advances in Neural Information Processing Systems 36, 2024 | 6 | 2024 |
| Adapting fairness interventions to missing values R Feng, F Calmon, H Wang Advances in Neural Information Processing Systems 36, 2024 | 3 | 2024 |
| The impact of split classifiers on group fairness H Wang, H Hsu, M Diaz, FP Calmon 2021 IEEE International Symposium on Information Theory (ISIT), 3179-3184, 2021 | 3 | 2021 |
| Private Synthetic Data Meets Ensemble Learning H Sun, N Azizan, A Srivastava, H Wang arXiv preprint arXiv:2310.09729, 2023 | 1 | 2023 |
| Quantifying Representation Reliability in Self-Supervised Learning Models YJ Park, H Wang, S Ardeshir, N Azizan arXiv preprint arXiv:2306.00206, 2023 | 1* | 2023 |
| Analyzing generalization of neural networks through loss path kernels Y Chen, W Huang, H Wang, C Loh, A Srivastava, L Nguyen, L Weng Advances in Neural Information Processing Systems 36, 2024 | | 2024 |
Flavio du Pin CalmonHarvard University在 seas.harvard.edu 的电子邮件经过验证
