Predictive low-rank decomposition for kernel
methods
(Cholesky with Side Information - CSI)
Last updated: May 26th, 2005
Description
Matlab
code - version 1.0
Future
improvements
Demos
The csi package is a Matlab program that implements the predictive low-rank decomposition for kernel matrices. The algorithm takes into account side information such as class labels or response variables in order to build the approximation of the kernel matrix
For more information, please read the
following paper:
Francis R. Bach, Michael I. Jordan.
Predictive low-rank decomposition for kernel methods.
Proceedings of the Twenty-second International
Conference on Machine Learning (ICML), 2005. [pdf]
Precise instructions on how to use the package as well as a demo script are included in the archive file. In short, to use it you will call csi() or csi_c(), supplying it with the kernel matrices you want to approximate. We provide a Matlab implementation csi() as well as a C implementation csi_c() that can be called directly from Matlab.
The csi package is Copyright (c) 2005 by Francis Bach. If you have any questions or comments regarding this package, or if you want to report any bugs, please send an e-mail to francis.bach@mines.org. The current version 1.0 has been released on May 26th 2005. Check this web page regularly for newer versions.