| Differentially private and fair deep learning: A lagrangian dual approach C Tran, F Fioretto, P Van Hentenryck Proceedings of the AAAI Conference on Artificial Intelligence 35 (11), 9932-9939, 2021 | 88 | 2021 |
| Lagrangian duality for constrained deep learning F Fioretto, P Van Hentenryck, TWK Mak, C Tran, F Baldo, M Lombardi Machine Learning and Knowledge Discovery in Databases. Applied Data Science …, 2021 | 77 | 2021 |
| Differentially private empirical risk minimization under the fairness lens C Tran, M Dinh, F Fioretto Advances in Neural Information Processing Systems 34, 27555-27565, 2021 | 58 | 2021 |
| Differential privacy and fairness in decisions and learning tasks: A survey F Fioretto, C Tran, P Van Hentenryck, K Zhu arXiv preprint arXiv:2202.08187, 2022 | 57 | 2022 |
| Decision Making with Differential Privacy under a Fairness Lens. C Tran, F Fioretto, P Van Hentenryck, Z Yao IJCAI, 560-566, 2021 | 34 | 2021 |
| Pruning has a disparate impact on model accuracy C Tran, F Fioretto, JE Kim, R Naidu Advances in neural information processing systems 35, 17652-17664, 2022 | 25 | 2022 |
| A fairness analysis on private aggregation of teacher ensembles C Tran, MH Dinh, K Beiter, F Fioretto arXiv preprint arXiv:2109.08630, 2021 | 11 | 2021 |
| Decision making with differential privacy under a fairness lens F Fioretto, C Tran, P Van Hentenryck arXiv preprint arXiv:2105.07513, 2021 | 11 | 2021 |
| SF-PATE: scalable, fair, and private aggregation of teacher ensembles C Tran, K Zhu, F Fioretto, P Van Hentenryck arXiv preprint arXiv:2204.05157, 2022 | 10 | 2022 |
| Fairness increases adversarial vulnerability C Tran, K Zhu, F Fioretto, P Van Hentenryck arXiv preprint arXiv:2211.11835, 2022 | 9 | 2022 |
| Gaussian process for noisy inputs with ordering constraints C Tran, V Pavlovic, R Kopp arXiv preprint arXiv:1507.00052, 2015 | 7 | 2015 |
| Privacy-preserving and accountable multi-agent learning A Nagar, C Tran, F Fioretto AAMAS Conference proceedings, 2021 | 6 | 2021 |
| A lagrangian dual framework for deep neural networks with constraints F Fioretto, TW Mak, F Baldo, M Lombardi, P Van Hentenryck arXiv preprint arXiv:2001.09394, 2020 | 6 | 2020 |
| Personalized privacy auditing and optimization at test time C Tran, F Fioretto arXiv preprint arXiv:2302.00077, 2023 | 4 | 2023 |
| On the fairness impacts of private ensembles models C Tran, F Fioretto arXiv preprint arXiv:2305.11807, 2023 | 3 | 2023 |
| Folded optimization for end-to-end model-based learning J Kotary, MH Dinh, F Fioretto, J Kotary, V Di Vito, F Fioretto, C Tran, ... International Joint Conference on Artificial Intelligence (IJCAI) 35, 179-225, 2023 | 3 | 2023 |
| Unsupervised domain adaptation with copula models CD Tran, OO Rudovic, V Pavlovic 2017 IEEE 27th International Workshop on Machine Learning for Signal …, 2017 | 3 | 2017 |
| Intrusion detection under covariate shift using modified support vector machine and modified backpropagation TD Cuong, NL Giang Proceedings of the 3rd Symposium on Information and Communication Technology …, 2012 | 3 | 2012 |
| On The Fairness Impacts of Hardware Selection in Machine Learning SH Nelaturu, NK Ravichandran, C Tran, S Hooker, F Fioretto Forty-first International Conference on Machine Learning, 2023 | 2 | 2023 |
| The Data Minimization Principle in Machine Learning P Ganesh, C Tran, R Shokri, F Fioretto arXiv preprint arXiv:2405.19471, 2024 | | 2024 |
Pascal Van HentenryckGeorgia Institute of Technology在 isye.gatech.edu 的电子邮件经过验证
Pascal Van HentenryckGeorgia Institute of Technology在 isye.gatech.edu 的电子邮件经过验证