Redundancy reduction with information-preserving nonlinear maps
AbstractThe basic idea of linear principal component analysis (PCA) involves decorrelating coordinates by an orthogonal linear transformation. In this paper we generalize this i...
Publications
2 shownRedundancy reduction with information-preserving nonlinear maps
AbstractThe basic idea of linear principal component analysis (PCA) involves decorrelating coordinates by an orthogonal linear transformation. In this paper we generalize this i...
Frequent Co-Authors
Researcher Info
- h-index
- 2
- Publications
- 2
- Citations
- 50
- Institution
- Ludwig-Maximilians-Universität München
External Links
Impact Metrics
h-index
2
h-index: Number of publications with at least h citations each.