Multiple Kernel Testing for SVM-based System Identification
published: Jan. 12, 2011, recorded: December 2010, views: 290
Report a problem or upload filesIf you have found a problem with this lecture or would like to send us extra material, articles, exercises, etc., please use our ticket system to describe your request and upload the data.
Enter your e-mail into the 'Cc' field, and we will keep you updated with your request's status.
We apply methods of multiple kernel learning to the problem of system identification for multi-dimensional temporal data. Rather than building a full probabilistic model, we take a computationally simple approach that uses out of the box machine learning methods. We attempt to learn the covariance function of a stochastic process via multiple kernel learning. We achieve promising preliminary results and the work suggests an abundance of future theoretical work. We hope to draw on the theory of SVM methods to give a principled learning theory style description of system identification in stochastic processes.
Link this pageWould you like to put a link to this lecture on your homepage?
Go ahead! Copy the HTML snippet !