By Marcello Pelillo (Ed.),Marcello Pelillo
This obtainable text/reference provides a coherent assessment of the rising box of non-Euclidean similarity studying. The publication offers a large variety of views on similarity-based trend research and popularity equipment, from only theoretical demanding situations to sensible, real-world purposes. The assurance comprises either supervised and unsupervised studying paradigms, in addition to generative and discriminative versions. subject matters and contours: explores the origination and motives of non-Euclidean (dis)similarity measures, and the way they impact the functionality of conventional class algorithms; reports similarity measures for non-vectorial facts, contemplating either a “kernel tailoring” process and a method for studying similarities at once from education info; describes a variety of tools for “structure-preserving” embeddings of based facts; formulates classical trend popularity difficulties from a in basic terms game-theoretic point of view; examines large-scale biomedical imaging applications.
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Extra resources for Similarity-Based Pattern Analysis and Recognition (Advances in Computer Vision and Pattern Recognition)
Similarity-Based Pattern Analysis and Recognition (Advances in Computer Vision and Pattern Recognition) by Marcello Pelillo (Ed.),Marcello Pelillo