Talks and Poster Presentations (with Proceedings-Entry):
M. Reiter, T. Melzer:
"Ridge Penalty Regularization for kernel-CCA";
Talk: Austrian Association for Pattern Recognition (ÖAGM),
- 2004-06-18; in: "Proceedings of 28th Workshop",
Österreichische Computer Gesellschaft,
CCA and kernel-CCA are powerful statistical tools that have been successfully employed for feature extraction. However, when working in high-dimensional feature spaces, care has to be taken to avoid overfitting. This paper discusses the influence of ridge penalty regularization on kernel-CCA by relating it to multivariate linear regression (MLR) and partial least squares (PLS).
Experimental results for a pose estimation task are given.
Online library catalogue of the TU Vienna:
Electronic version of the publication:
Created from the Publication Database of the Vienna University of Technology.