Predictive low-rank decomposition for kernel methods - CSI

Predictive low-rank decomposition for kernel methods
(Cholesky with Side Information - CSI)
 Last updated: May 26th, 2005

Matlab code - version 1.0
Future improvements


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]

Matlab code - version 1.0

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 The current version 1.0 has been released on May 26th 2005. Check this web page regularly for newer versions.

csi version 1.0