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Multi Facet Learning in Hilbert Spaces

Kondor, Risi; Csányi, Gábor; Ahnert, Sebastian E.; Jebara, Tony

We extend the kernel based learning framework to learning from linear functionals, such as partial derivatives. The learning problem is formulated as a generalized regularized risk minimization problem, possibly involving several different functionals. We show how to reduce this to conventional kernel based learning methods and explore a specific application in Computational Condensed Matter Physics.



More About This Work

Academic Units
Computer Science
Department of Computer Science, Columbia University
Columbia University Computer Science Technical Reports, CUCS-054-05
Published Here
April 21, 2011
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