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2020 – today
- 2024
[j5]Christophe Denis, Romuald Elie, Mohamed Hebiri, François Hu:
Fairness guarantees in multi-class classification with demographic parity. J. Mach. Learn. Res. 25: 130:1-130:46 (2024)- [j4]Christophe Denis, Mohamed Hebiri, Boris Ndjia Njike
, Xavier Siebert:
Active learning algorithm through the lens of rejection arguments. Mach. Learn. 113(2): 753-788 (2024) - [i7]Florian Valade, Mohamed Hebiri, Paul Gay:
EERO: Early Exit with Reject Option for Efficient Classification with limited budget. CoRR abs/2402.03779 (2024) - [i6]Evgenii Chzhen, Mohamed Hebiri, Gayane Taturyan:
Regression under demographic parity constraints via unlabeled post-processing. CoRR abs/2407.15453 (2024) - 2021
- [i5]Evgenii Chzhen, Christophe Denis, Mohamed Hebiri, Titouan Lorieul:
Set-valued classification - overview via a unified framework. CoRR abs/2102.12318 (2021) - 2020
- [c6]Evgenii Chzhen, Christophe Denis, Mohamed Hebiri, Luca Oneto, Massimiliano Pontil:
Fair regression with Wasserstein barycenters. NeurIPS 2020 - [c5]Evgenii Chzhen, Christophe Denis, Mohamed Hebiri, Luca Oneto, Massimiliano Pontil:
Fair regression via plug-in estimator and recalibration with statistical guarantees. NeurIPS 2020 - [c4]Ahmed Zaoui, Christophe Denis, Mohamed Hebiri:
Regression with reject option and application to kNN. NeurIPS 2020 - [i4]Evgenii Chzhen, Christophe Denis, Mohamed Hebiri, Luca Oneto, Massimiliano Pontil:
Fair Regression with Wasserstein Barycenters. CoRR abs/2006.07286 (2020) - [i3]Mohamed Hebiri, Johannes Lederer:
Layer Sparsity in Neural Networks. CoRR abs/2006.15604 (2020) - [i2]Christophe Denis, Mohamed Hebiri, Ahmed Zaoui:
Regression with reject option and application to kNN. CoRR abs/2006.16597 (2020)
2010 – 2019
- 2019
- [c3]Evgenii Chzhen, Christophe Denis, Mohamed Hebiri, Luca Oneto, Massimiliano Pontil:
Leveraging Labeled and Unlabeled Data for Consistent Fair Binary Classification. NeurIPS 2019: 12739-12750 - 2017
- [j3]Christophe Denis, Mohamed Hebiri:
Confidence Sets with Expected Sizes for Multiclass Classification. J. Mach. Learn. Res. 18: 102:1-102:28 (2017) - [i1]Evgenii Chzhen, Christophe Denis, Mohamed Hebiri, Joseph Salmon:
On the benefits of output sparsity for multi-label classification. CoRR abs/1703.04697 (2017) - 2015
- [c2]Christophe Denis, Mohamed Hebiri:
Confidence Sets for Classification. SLDS 2015: 301-312 - 2013
- [j2]Mohamed Hebiri, Johannes Lederer:
How Correlations Influence Lasso Prediction. IEEE Trans. Inf. Theory 59(3): 1846-1854 (2013) - [c1]Arnak S. Dalalyan, Mohamed Hebiri, Katia Meziani, Joseph Salmon:
Learning Heteroscedastic Models by Convex Programming under Group Sparsity. ICML (3) 2013: 379-387 - 2010
- [j1]Mohamed Hebiri:
Sparse conformal predictors. Stat. Comput. 20(2): 253-266 (2010)
Coauthor Index
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