1 code implementation • 11 Oct 2023 • 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 jointly.
1 code implementation • 10 Feb 2023 • Fabien Girka, Arnaud Gloaguen, Laurent Le Brusquet, Violetta Zujovic, Arthur Tenenhaus
Regularized Generalized Canonical Correlation Analysis (RGCCA) is a general statistical framework for multi-block data analysis.
no code implementations • 17 Nov 2016 • Wacha Bounliphone, Eugene Belilovsky, Arthur Tenenhaus, Ioannis Antonoglou, Arthur Gretton, Matthew B. Blashcko
The second test, called the relative test of similarity, is use to determine which of the two samples from arbitrary distributions is significantly closer to a reference sample of interest and the relative measure of similarity is based on the Maximum Mean Discrepancy (MMD).
no code implementations • 29 Oct 2016 • Tommy Löfstedt, Fouad Hadj-Selem, Vincent Guillemot, Cathy Philippe, Nicolas Raymond, Edouard Duchesney, Vincent Frouin, Arthur Tenenhaus
However, for technical reasons, the variable selection offered by SGCCA was restricted to a covariance link between the blocks (i. e., with $\tau=1$).
1 code implementation • 15 Jun 2014 • Wacha Bounliphone, Arthur Gretton, Arthur Tenenhaus, Matthew Blaschko
Such a test enables us to determine whether one source variable is significantly more dependent on a first target variable or a second.