Mohamed Hebiri

According to our database, Mohamed Hebiri authored at least 16 papers between 2010 and 2024.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of four.

2024

Active learning algorithm through the lens of rejection arguments.

Christophe Denis, Mohamed Hebiri, Boris Ndjia Njike, Xavier Siebert

Mach. Learn., February, 2024

Fairness guarantees in multi-class classification with demographic parity.

Christophe Denis, Romuald Elie, Mohamed Hebiri, François Hu

J. Mach. Learn. Res., 2024

Regression under demographic parity constraints via unlabeled post-processing.

Evgenii Chzhen, Mohamed Hebiri, Gayane Taturyan

CoRR, 2024

EERO: Early Exit with Reject Option for Efficient Classification with limited budget.

Florian Valade, Mohamed Hebiri, Paul Gay

CoRR, 2024

2021

Set-valued classification - overview via a unified framework.

Evgenii Chzhen, Christophe Denis, Mohamed Hebiri, Titouan Lorieul

CoRR, 2021

2020

Layer Sparsity in Neural Networks.

Mohamed Hebiri, Johannes Lederer

CoRR, 2020

Regression with reject option and application to kNN.

Ahmed Zaoui, Christophe Denis, Mohamed Hebiri

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Fair regression via plug-in estimator and recalibration with statistical guarantees.

Evgenii Chzhen, Christophe Denis, Mohamed Hebiri, Luca Oneto, Massimiliano Pontil

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Fair regression with Wasserstein barycenters.

Evgenii Chzhen, Christophe Denis, Mohamed Hebiri, Luca Oneto, Massimiliano Pontil

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

2019

Leveraging Labeled and Unlabeled Data for Consistent Fair Binary Classification.

Evgenii Chzhen, Christophe Denis, Mohamed Hebiri, Luca Oneto, Massimiliano Pontil

Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

2017

Confidence Sets with Expected Sizes for Multiclass Classification.

Christophe Denis, Mohamed Hebiri

J. Mach. Learn. Res., 2017

On the benefits of output sparsity for multi-label classification.

Evgenii Chzhen, Christophe Denis, Mohamed Hebiri, Joseph Salmon

CoRR, 2017

2015

Confidence Sets for Classification.

Christophe Denis, Mohamed Hebiri

Proceedings of the Statistical Learning and Data Sciences - Third International Symposium, 2015

2013

How Correlations Influence Lasso Prediction.

Mohamed Hebiri, Johannes Lederer

IEEE Trans. Inf. Theory, 2013

Learning Heteroscedastic Models by Convex Programming under Group Sparsity.

Arnak S. Dalalyan, Mohamed Hebiri, Katia Meziani, Joseph Salmon

Proceedings of the 30th International Conference on Machine Learning, 2013

2010

Sparse conformal predictors.

Mohamed Hebiri

Stat. Comput., 2010