4 citations · 11 across the 8 of their papers we have counts for
8 papers
Latent Functional PARAFAC for modeling multidimensional longitudinal data
Lucas Sort, Laurent Le Brusquet, Arthur Tenenhaus
In numerous settings, it is increasingly common to deal with longitudinal data organized as high-dimensional multi-dimensional arrays, also known as tensors. Within this framework,…
Functional Generalized Canonical Correlation Analysis for studying multiple longitudinal variables
Lucas Sort, Laurent Le Brusquet, Arthur Tenenhaus
In this paper, we introduce Functional Generalized Canonical Correlation Analysis (FGCCA), a new framework for exploring associations between multiple random processes observed joi…
Tensor Generalized Canonical Correlation Analysis
Fabien Girka, Arnaud Gloaguen, Laurent Le Brusquet +2
Regularized Generalized Canonical Correlation Analysis (RGCCA) is a general statistical framework for multi-block data analysis. RGCCA enables deciphering relationships between sev…
Fast Non-Parametric Tests of Relative Dependency and Similarity
Wacha Bounliphone, Eugene Belilovsky, Arthur Tenenhaus +3
We introduce two novel non-parametric statistical hypothesis tests. The first test, called the relative test of dependency, enables us to determine whether one source variable is s…
A general multiblock method for structured variable selection
Tommy Löfstedt, Fouad Hadj-Selem, Vincent Guillemot +5
Regularised canonical correlation analysis was recently extended to more than two sets of variables by the multiblock method Regularised generalised canonical correlation analysis…
Regularized Consensus PCA
Michel Tenenhaus, Arthur Tenenhaus, Patrick J. F. Groenen
A new framework for many multiblock component methods (including consensus and hierarchical PCA) is proposed. It is based on the consensus PCA model: a scheme connecting each block…
Jointly Sparse Global SIMPLS Regression
Tzu-Yu Liu, Laura Trinchera, Arthur Tenenhaus +2
Partial least squares (PLS) regression combines dimensionality reduction and prediction using a latent variable model. Since partial least squares regression (PLS-R) does not requi…
A low variance consistent test of relative dependency
Wacha Bounliphone, Arthur Gretton, Arthur Tenenhaus +1
We describe a novel non-parametric statistical hypothesis test of relative dependence between a source variable and two candidate target variables. Such a test enables us to determ…