Mohamed Hebiri

发表

Some theoretical results on the Grouped Variables Lasso

C. Chesneau, Mohamed Hebiri, 2008 .

On the Prediction Performance of the Lasso

A. Dalalyan, Mohamed Hebiri, Johannes Lederer, 2014, 1402.1700.

The Smooth-Lasso and other ℓ1+ℓ2-penalized methods

S. Geer, Mohamed Hebiri, 2011 .

The Smooth-Lasso and other ℓ1+ℓ2-penalized methods

S. Geer, Mohamed Hebiri, 2011 .

Consistency of plug-in confidence sets for classification in semi-supervised learning

Mohamed Hebiri, C. Denis, Christophe Denis, 2015, Journal of Nonparametric Statistics.

Confidence Sets with Expected Sizes for Multiclass Classification

Christophe Denis, Mohamed Hebiri, Mohamed Hebiri, 2016, J. Mach. Learn. Res..

Rank penalized estimation of a quantum system

Pierre Alquier, Mohamed Hebiri, C. Butucea, 2012, 1206.1711.

On Lasso refitting strategies

Mohamed Hebiri, J. Salmon, Evgenii Chzhen, 2017, Bernoulli.

Minimax semi-supervised confidence sets for multi-class classification

Evgenii Chzhen, Mohamed Hebiri, Christophe Denis, 2019, 1904.12527.

Transductive versions of the LASSO and the Dantzig Selector

Pierre Alquier, Mohamed Hebiri, Pierre Alquier, 2009, Journal of Statistical Planning and Inference.

Fairness guarantee in multi-class classification

Mohamed Hebiri, C. Denis, R. Elie, 2021, 2109.13642.

On the Prediction Performance of the Lasso

A. Dalalyan, Mohamed Hebiri, Johannes Lederer, 2014, 1402.1700.

Active learning algorithm through the lens of rejection arguments

Boris Ndjia Njike, Mohamed Hebiri, C. Denis, 2022, 2208.14682.

Generalization of constraints for high dimensional regression problems

Pierre Alquier, Mohamed Hebiri, 2008, Statistics & Probability Letters.

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

Luca Oneto, Massimiliano Pontil, Evgenii Chzhen, 2020, NeurIPS.

Learning Heteroscedastic Models by Convex Programming under Group Sparsity

Mohamed Hebiri, Arnak S. Dalalyan, Joseph Salmon, 2013, ICML.

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

Evgenii Chzhen, Christophe Denis, Mohamed Hebiri, 2017, ArXiv.

How Correlations Influence Lasso Prediction

Mohamed Hebiri, Johannes Lederer, Mohamed Hebiri, 2012, IEEE Transactions on Information Theory.

Leveraging Labeled and Unlabeled Data for Consistent Fair Binary Classification

Luca Oneto, Massimiliano Pontil, Evgenii Chzhen, 2019, NeurIPS.

Sparse conformal predictors

Mohamed Hebiri, Mohamed Hebiri, 2009, Stat. Comput..

Fairness guarantee in multi-class classification

Mohamed Hebiri, C. Denis, R. Elie, 2021, 2109.13642.

Set-valued classification - overview via a unified framework pdf

Evgenii Chzhen, Mohamed Hebiri, Titouan Lorieul, 2021, ArXiv.

Fair Regression with Wasserstein Barycenters pdf

Luca Oneto, Massimiliano Pontil, Evgenii Chzhen, 2020, NeurIPS.

Regression with reject option and application to kNN pdf

Christophe Denis, Mohamed Hebiri, Ahmed Zaoui, 2020, NeurIPS.

Layer Sparsity in Neural Networks pdf

Mohamed Hebiri, Johannes Lederer, Mohamed Hebiri, 2020, ArXiv.

The Smooth-Lasso and other $\ell_1+\ell_2$-penalized methods

Mohamed Hebiri, S. Geer, Mohamed Hebiri, 2010, 1003.4885.

Sparse conformal predictors

Mohamed Hebiri, 2009, Statistics and computing.

Regularization with the Smooth-Lasso procedure

Mohamed Hebiri, Mohamed Hebiri, 2008, 0803.0668.

Learning Heteroscedastic Models by Convex Programming under Group Sparsity

A. Dalalyan, Mohamed Hebiri, J. Salmon, 2013, ICML.

Confidence Sets for Classification

Christophe Denis, Mohamed Hebiri, Mohamed Hebiri, 2015, SLDS.

Aggregation for Linear Inverse Problems

Mohamed Hebiri, Jean-Michel Loubes, P. Rochet, 2014 .

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

Mohamed Hebiri, Florian Valade, Paul Gay, 2024, ArXiv.