This book constitutes the refereed proceedings of the 13th International Conference on Machine Learning and Cybernetics, Lanzhou, China, in July 2014. The 45 revised full papers presented were carefully reviewed and selected from 421 submissions. The papers are organized in topical sections on classification and semi-supervised learning; clustering and kernel; application to recognition; sampling and big data; application to detection; decision tree learning; learning and adaptation; similarity and decision making; learning with uncertainty; improved learning algorithms and applications.
This book constitutes the refereed proceedings of the 13th International Conference on Machine Learning and Cybernetics, Lanzhou, China, in July 2014. The 45 revised full papers presented were carefully reviewed and selected from 421 submissions. The papers are organized in topical sections on classification and semi-supervised learning; clustering and kernel; application to recognition; sampling and big data; application to detection; decision tree learning; learning and adaptation; similarity and decision making; learning with uncertainty; improved learning algorithms and applications.
Produktdetails
Produktdetails
Communications in Computer and Information Science 481
Artikelnr. des Verlages: 86391228, 978-3-662-45651-4
2014
Seitenzahl: 476
Erscheinungstermin: 17. Dezember 2014
Englisch
Abmessung: 235mm x 155mm x 26mm
Gewicht: 715g
ISBN-13: 9783662456514
ISBN-10: 3662456516
Artikelnr.: 41649962
Inhaltsangabe
Classification and semi-supervised learning;.- Clustering and kernel.-Application to recognition.- Sampling and big data.- Application to detection.- Decision tree learning; learning and adaptation.- Similarity and decision making.- Learning with uncertainty.- Improved learning algorithms and applications.
Classification and semi-supervised learning;.- Clustering and kernel.-Application to recognition.- Sampling and big data.- Application to detection.- Decision tree learning; learning and adaptation.- Similarity and decision making.- Learning with uncertainty.- Improved learning algorithms and applications.
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