Mohamed Hebiri

According to our database1, Mohamed Hebiri authored at least 14 papers between 2010 and 2024.

Collaborative distances:
  • Dijkstra number2 of five.
  • Erdős number3 of four.

Timeline

Legend:

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PhD thesis 
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Links

On csauthors.net:

Bibliography

2024
Active learning algorithm through the lens of rejection arguments.
Mach. Learn., February, 2024

EERO: Early Exit with Reject Option for Efficient Classification with limited budget.
CoRR, 2024

2021
Set-valued classification - overview via a unified framework.
CoRR, 2021

2020
Layer Sparsity in Neural Networks.
CoRR, 2020

Regression with reject option and application to kNN.
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.
Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Fair regression with Wasserstein barycenters.
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.
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.
J. Mach. Learn. Res., 2017

On the benefits of output sparsity for multi-label classification.
CoRR, 2017

2015
Confidence Sets for Classification.
Proceedings of the Statistical Learning and Data Sciences - Third International Symposium, 2015

2013
How Correlations Influence Lasso Prediction.
IEEE Trans. Inf. Theory, 2013

Learning Heteroscedastic Models by Convex Programming under Group Sparsity.
Proceedings of the 30th International Conference on Machine Learning, 2013

2010
Sparse conformal predictors.
Stat. Comput., 2010


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