A Kernel Random Matrix-Based Approach for Sparse PCA.
Mohamed El Amine SeddikMohamed TamaazoustiRomain CouilletPublished in: ICLR (Poster) (2019)
Keyphrases
- sparse pca
- positive definite
- direct optimization
- semidefinite programming
- kernel matrix
- kernel methods
- kernel function
- covariance matrix
- feature selection
- principle component analysis
- feature space
- reproducing kernel hilbert space
- support vector
- singular value decomposition
- low rank
- anomaly detection
- linear programming