166 citations · 317 across the 26 of their papers we have counts for
3 papers · 1 filter
Layer Sparsity in Neural Networks
Mohamed Hebiri, Johannes Lederer
Sparsity has become popular in machine learning, because it can save computational resources, facilitate interpretations, and prevent overfitting. In this paper, we discuss sparsit…
Fair Regression with Wasserstein Barycenters
Evgenii Chzhen, Christophe Denis, Mohamed Hebiri +2
We study the problem of learning a real-valued function that satisfies the Demographic Parity constraint. It demands the distribution of the predicted output to be independent of t…
Regression with reject option and application to kNN
Christophe Denis, Mohamed Hebiri, Ahmed Zaoui
We investigate the problem of regression where one is allowed to abstain from predicting. We refer to this framework as regression with reject option as an extension of classificat…