6 citations · 9 across the 5 of their papers we have counts for
5 papers
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…
Covariance constraints for stochastic inverse problems of computer models
Nicolas Bousquet, Mélanie Blazère, Thomas Cerbelaud
Stochastic inverse problems considered in this article consist of estimating the probability distributions of intrinsically random inputs of computer models. These estimations are…
A unified framework for the study of the PLS estimator's properties
Mélanie Blazère, Fabrice Gamboa, Jean-Michel Loubes
In this paper we propose a new approach to study the properties of the Partial Least Squares (PLS) estimator. This approach relies on the link between PLS and discrete orthogonal p…
PLS: a new statistical insight through the prism of orthogonal polynomials
Mélanie Blazère, Fabrice Gamboa, Jean-Michel Loubes
Partial Least Square (PLS) is a dimension reduction method used to remove multicollinearities in a regression model. However contrary to Principal Components Analysis (PCA) the PLS…
Group Lasso for generalized linear models in high dimension
Mélanie Blazère, Jean-Michel Loubes, Fabrice Gamboa
Nowadays an increasing amount of data is available and we have to deal with models in high dimension (number of covariates much larger than the sample size). Under sparsity assumpt…