By Marcello Pelillo (auth.), Marcello Pelillo (eds.)
This obtainable text/reference offers a coherent assessment of the rising box of non-Euclidean similarity studying. The ebook provides a wide variety of views on similarity-based trend research and popularity equipment, from in simple terms theoretical demanding situations to functional, real-world functions. The insurance comprises either supervised and unsupervised studying paradigms, in addition to generative and discriminative versions. themes and lines: explores the origination and reasons of non-Euclidean (dis)similarity measures, and the way they impact the functionality of conventional type algorithms; experiences similarity measures for non-vectorial info, contemplating either a “kernel tailoring” technique and a technique for studying similarities at once from education facts; describes a variety of equipment for “structure-preserving” embeddings of dependent facts; formulates classical trend attractiveness difficulties from a basically game-theoretic viewpoint; examines large-scale biomedical imaging applications.
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