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Conference papers
Optimal Feature Representation for Kernel Machines using Kernel-Target Alignment Criterion
Abstract : Kernel-target alignment is commonly used to predict the behavior of any given reproducing kernel in a classification context, without training any kernel machine. In this paper, we present a gradient ascent algorithm for maximizing the alignment over linear transform of the input space. Our method is compared to the minimization of the radius-margin bound. Experimental results on multi-dimensional benchmarks show the effectiveness of our approach.
https://hal-utt.archives-ouvertes.fr/hal-02356442
Contributor : Jean-Baptiste Vu Van Connect in order to contact the contributor
Submitted on : Friday, November 8, 2019 - 5:19:12 PM
Last modification on : Thursday, November 18, 2021 - 4:00:07 PM
Contributor : Jean-Baptiste Vu Van Connect in order to contact the contributor
Submitted on : Friday, November 8, 2019 - 5:19:12 PM
Last modification on : Thursday, November 18, 2021 - 4:00:07 PM