
A kernel random matrix-based approach for sparse PCA
Author(s) -
Mohamed El Amine Seddik,
Mohamed Tamaazousti,
Romain Couillet
Publication year - 2019
Publication title -
hal (le centre pour la communication scientifique directe)
Language(s) - English
Resource type - Conference proceedings
Subject(s) - kernel principal component analysis , principal component analysis , sparse pca , kernel (algebra) , mathematics , random matrix , covariance matrix , differentiable function , sparse matrix , pattern recognition (psychology) , matrix (chemical analysis) , gaussian , algorithm , computer science , combinatorics , artificial intelligence , kernel method , support vector machine , eigenvalues and eigenvectors , statistics , pure mathematics , physics , quantum mechanics , materials science , composite material