| Fair regression with wasserstein barycenters E Chzhen, C Denis, M Hebiri, L Oneto, M Pontil Advances in Neural Information Processing Systems 33, 7321-7331, 2020 | 113 | 2020 |
| Leveraging labeled and unlabeled data for consistent fair binary classification E Chzhen, C Denis, M Hebiri, L Oneto, M Pontil Advances in Neural Information Processing Systems 32, 2019 | 107 | 2019 |
| Fair regression via plug-in estimator and recalibration with statistical guarantees E Chzhen, C Denis, M Hebiri, L Oneto, M Pontil Advances in Neural Information Processing Systems 33, 19137-19148, 2020 | 51 | 2020 |
| Set-valued classification--overview via a unified framework E Chzhen, C Denis, M Hebiri, T Lorieul arXiv preprint arXiv:2102.12318, 2021 | 42 | 2021 |
| A minimax framework for quantifying risk-fairness trade-off in regression E Chzhen, N Schreuder The Annals of Statistics 50 (4), 2416-2442, 2022 | 34 | 2022 |
| Classification with abstention but without disparities N Schreuder, E Chzhen Uncertainty in Artificial Intelligence, 1227-1236, 2021 | 27 | 2021 |
| A gradient estimator via L1-randomization for online zero-order optimization with two point feedback A Akhavan, E Chzhen, M Pontil, A Tsybakov Advances in Neural Information Processing Systems 35, 7685-7696, 2022 | 22 | 2022 |
| On lasso refitting strategies E Chzhen, M Hebiri, J Salmon Bernoulli 25 (4A), 3175-3200, 2019 | 17 | 2019 |
| Minimax semi-supervised set-valued approach to multi-class classification E Chzhen, C Denis, M Hebiri Bernoulli 27 (4), 2389-2412, 2021 | 15* | 2021 |
| Fair learning with Wasserstein barycenters for non-decomposable performance measures S Gaucher, N Schreuder, E Chzhen International Conference on Artificial Intelligence and Statistics, 2436-2459, 2023 | 10 | 2023 |
| Gradient-free optimization of highly smooth functions: improved analysis and a new algorithm A Akhavan, E Chzhen, M Pontil, AB Tsybakov arXiv preprint arXiv:2306.02159, 2023 | 9 | 2023 |
| A unified approach to fair online learning via blackwell approachability E Chzhen, C Giraud, G Stoltz Advances in Neural Information Processing Systems 34, 18280-18292, 2021 | 9 | 2021 |
| On the benefits of output sparsity for multi-label classification E Chzhen, C Denis, M Hebiri, J Salmon arXiv preprint arXiv:1703.04697, 2017 | 7 | 2017 |
| An example of prediction which complies with Demographic Parity and equalizes group-wise risks in the context of regression E Chzhen, N Schreuder AFCI at NeurIPS 2020, 2020 | 5 | 2020 |
| Optimal rates for nonparametric f-score binary classification via post-processing E Chzhen Mathematical Methods of Statistics 29, 87-105, 2020 | 4* | 2020 |
| Plug-in methods in classification E Chzhen Université Paris-Est, 2019 | 4 | 2019 |
| SignSVRG: fixing SignSGD via variance reduction E Chzhen, S Schechtman arXiv preprint arXiv:2305.13187, 2023 | 2 | 2023 |
| Classification of sparse binary vectors E Chzhen arXiv preprint arXiv:1903.11867, 2019 | 2 | 2019 |
| Small total-cost constraints in contextual bandits with knapsacks, with application to fairness E Chzhen, C Giraud, Z Li, G Stoltz Advances in Neural Information Processing Systems 36, 2024 | 1 | 2024 |
| Parameter-free projected gradient descent E Chzhen, C Giraud, G Stoltz arXiv preprint arXiv:2305.19605, 2023 | 1 | 2023 |
Mohamed HebiriUniversité Paris-Est -- Marne-la-Vallée在 u-pem.fr 的电子邮件经过验证
