abstract
- Kernel supervised principal component analysis (KSPCA) is a computationally efficient supervised feature extraction method that can learn non-linear transformations. We start the study of the stati...
A Dimension-Independent Generalization Bound for Kernel Supervised Principal Component Analysis
Conferences
- Overview
- Additional Document Info
- View All
Overview
authors
publication date
- December 2015