3 citations · 4 across the 2 of their papers we have counts for
2 papers
stat.AP2015★ 3 cited
Using the LASSO for gene selection in bladder cancer data
Stéphane Chrétien, Christophe Guyeux, Michael Boyer-Guittaut +2
Given a gene expression data array of a list of bladder cancer patients with their tumor states, it may be difficult to determine which genes can operate as disease markers when th…
stat.CO2015★ 1 cited
A Bregman Proximal ADMM for NMF with Outliers: Estimating features with missing values and outliers: a Bregman-proximal point algorithm for robust Non-negative Matrix Factorization with application to gene expression analysis
Stéphane Chrétien, Christophe Guyeux, Bastien Conesa +4
To extract the relevant features in a given dataset is a difficult task, recently resolved in the non-negative data case with the Non-negative Matrix factorization (NMF) method. Th…