17 citations · 41 across the 9 of their papers we have counts for
5 papers · 1 filter
Leveraging Labeled and Unlabeled Data for Consistent Fair Binary Classification
Evgenii Chzhen, Christophe Denis, Mohamed Hebiri +2
We study the problem of fair binary classification using the notion of Equal Opportunity. It requires the true positive rate to distribute equally across the sensitive groups. With…
Optimal rates for F-score binary classification
Evgenii Chzhen
We study the minimax settings of binary classification with F-score under the -smoothness assumptions on the regression function for $x \in \mat…
Minimax semi-supervised confidence sets for multi-class classification
Evgenii Chzhen, Christophe Denis, Mohamed Hebiri
In this work we study the semi-supervised framework of confidence set classification with controlled expected size in minimax settings. We obtain semi-supervised minimax rates of c…
Classification of sparse binary vectors
Evgenii Chzhen
In this work we consider a problem of multi-label classification, where each instance is associated with some binary vector. Our focus is to find a classifier which minimizes false…
On the benefits of output sparsity for multi-label classification
Evgenii Chzhen, Christophe Denis, Mohamed Hebiri +1
The multi-label classification framework, where each observation can be associated with a set of labels, has generated a tremendous amount of attention over recent years. The moder…