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Abstract: This paper addresses the kernel matrix learning problem in kernel methods. We model the kernel matrix as a random positive definite matrix following the Wishart distribution, with the parameter matrix of the Wishart distribution represented as a linear combination of mutually independent matrices with their own Wishart distributions. This defines a probabilistic mixture model of kernels that can be represented as a hierarchical model involving three levels, relating the target kernel... (Update)
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BibTeX entry: (Update)
@misc{ zhang-probabilistic,
author = "Zhihua Zhang and Dit-Yan Yeung and and James T. Kwok",
title = "Probabilistic Kernel Matrix Learning with a Mixture Model of Kernels",
url = "citeseer.ist.psu.edu/704161.html" }
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