| On the prediction performance of the lasso AS Dalalyan, M Hebiri, J Lederer | 205 | 2017 |
| The Smooth-Lasso and other ℓ1+ℓ2-penalized methods M Hebiri, S Van De Geer | 146 | 2011 |
| How correlations influence lasso prediction M Hebiri, J Lederer IEEE Transactions on Information Theory 59 (3), 1846-1854, 2012 | 144 | 2012 |
| 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 | 115 | 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 |
| Some theoretical results on the grouped variables Lasso C Chesneau, M Hebiri Mathematical Methods of Statistics 17, 317-326, 2008 | 79 | 2008 |
| 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 | 52 | 2020 |
| Consistency of plug-in confidence sets for classification in semi-supervised learning C Denis, M Hebiri Journal of Nonparametric Statistics 32 (1), 42-72, 2020 | 48 | 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 |
| Fairness guarantee in multi-class classification C Denis, R Elie, M Hebiri, F Hu arXiv preprint arXiv:2109.13642, 2021 | 38 | 2021 |
| Confidence sets with expected sizes for multiclass classification C Denis, M Hebiri Journal of Machine Learning Research 18 (102), 1-28, 2017 | 36 | 2017 |
| Learning heteroscedastic models by convex programming under group sparsity A Dalalyan, M Hebiri, K Meziani, J Salmon International Conference on Machine Learning, 379-387, 2013 | 32 | 2013 |
| Regularization with the smooth-lasso procedure M Hebiri arXiv preprint arXiv:0803.0668, 2008 | 30 | 2008 |
| Regression with reject option and application to knn A Zaoui, C Denis, M Hebiri Advances in Neural Information Processing Systems 33, 20073-20082, 2020 | 27 | 2020 |
| Rank-penalized estimation of a quantum system P Alquier, C Butucea, M Hebiri, K Meziani, T Morimae Physical Review A—Atomic, Molecular, and Optical Physics 88 (3), 032113, 2013 | 27 | 2013 |
| On lasso refitting strategies E Chzhen, M Hebiri, J Salmon | 17 | 2019 |
| Sparse conformal predictors: SCP M Hebiri Statistics and Computing 20, 253-266, 2010 | 14 | 2010 |
| Layer sparsity in neural networks M Hebiri, J Lederer, M Taheri Journal of Statistical Planning and Inference 234, 106195, 2025 | 13 | 2025 |
| Regression with reject option and application to knn C Denis, M Hebiri, A Zaoui arXiv preprint arXiv:2006.16597, 2020 | 13 | 2020 |
| Transductive versions of the LASSO and the Dantzig Selector P Alquier, M Hebiri Journal of Statistical Planning and Inference 142 (9), 2485-2500, 2012 | 13 | 2012 |
