Binet-Cauchy Kernels

Part of Advances in Neural Information Processing Systems 17 (NIPS 2004)

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Alex Smola, S.v.n. Vishwanathan


We propose a family of kernels based on the Binet-Cauchy theorem and its ex- tension to Fredholm operators. This includes as special cases all currently known kernels derived from the behavioral framework, diffusion processes, marginalized kernels, kernels on graphs, and the kernels on sets arising from the subspace angle approach. Many of these kernels can be seen as the extrema of a new continuum of kernel functions, which leads to numerous new special cases. As an application, we apply the new class of kernels to the problem of clustering of video sequences with encouraging results.