NIPS2009_0135_slide - Analysis of SVM with Indefinite...

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Unformatted text preview: Analysis of SVM with Indefinite Kernels Y. Ying, C. Campbell and M. Girolami SVM classification with non-positive semi-definite (indefinite) kernel (min-max problem) [Luss & d’Aspremont, NIPS’07] Approximate approaches (smoothing techniques) PGM and ACCPM [Luss & d’Aspremont, NIPS’07] Semi-infinite quadratically constrained linear programming (SIQCLP) [Chen & Ye, ICML’08] Our Contribution We prove that the objective function is, indeed, differentiable with Lipschitz continuous gradient We successfully apply Nesterov’s smoothing optimization approach to efficiently solve SVM with indefinite kernels ...
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