9 citations · 11 across the 4 of their papers we have counts for
8 papers
A survey of Identification and mitigation of Machine Learning algorithmic biases in Image Analysis
Laurent Risser, Agustin Picard, Lucas Hervier +1
The problem of algorithmic bias in machine learning has gained a lot of attention in recent years due to its concrete and potentially hazardous implications in society. In much the…
Robust spectral clustering using LASSO regularization
Camille Champion, Blazère Mélanie, Burcelin Rémy +2
Cluster structure detection is a fundamental task for the analysis of graphs, in order to understand and to visualize their functional characteristics. Among the different cluster…
A survey of bias in Machine Learning through the prism of Statistical Parity for the Adult Data Set
Philippe Besse, Eustasio del Barrio, Paula Gordaliza +2
Applications based on Machine Learning models have now become an indispensable part of the everyday life and the professional world. A critical question then recently arised among…
COREclust: a new package for a robust and scalable analysis of complex data
Camille Champion, Anne-Claire Brunet, Jean-Michel Loubes +1
In this paper, we present a new R package COREclust dedicated to the detection of representative variables in high dimensional spaces with a potentially limited number of observati…
Online Barycenter Estimation of Large Weighted Graphs
Ioana Gavra, Laurent Risser
In this paper, we propose a new method to compute the barycenter of large weighted graphs endowed with probability measures on their nodes. We suppose that the edge weights are dis…
Cytometry inference through adaptive atomic deconvolution
Manon Costa, Sébastien Gadat, Pauline Gonnord +1
In this paper we consider a statistical estimation problem known as atomic deconvolution. Introduced in reliability, this model has a direct application when considering biological…