Prof. Dr. Klaus-Robert Müller
University of Potsdam and Fraunhofer Institut FIRST
Kernel-based Learning Machines and Applications
Abstract: This lecture provides an introduction to Support Vector Machines and Kernel PCA as examples for successful kernel-based learning methods. We will give a short background about VC theory and kernel feature spaces and then proceed to kernel based learning in supervised scenarios including practical and algorithmic considerations. The usefulness of machine learning techniques is illustrated by examples from two different fields, namely Brain Computer Interfacing and the analysis of socio-economical data.
| Zeit: | Freitag, 10. Juni, 2005, 14.15 (Kaffee/Tee um 15.30) |
| Ort: | FU Berlin, Arnimallee 2-6, Raum 032 im EG |