Partially Supervised Learning - First IAPR TC3 Workshop, PSL 2011, Ulm, Germany, September 15-16, 2011, Revised Selected Papers (Paperback, 2012)

This book constitutes thoroughly refereed revised selected papers from the First IAPR TC3 Workshop on Partially Supervised Learning, PSL 2011, held in Ulm, Germany, in September 2011. The 14 papers presented in this volume were carefully reviewed and selected for inclusion in the book, which also includes 3 invited talks. PSL 2011 dealt with methodological issues as well as real-world applications of PSL. The main methodological issues were: combination of supervised and unsupervised learning; diffusion learning; semi-supervised classification, regression, and clustering; learning with deep architectures; active learning; PSL with vague, fuzzy, or uncertain teaching signals; learning, or statistical pattern recognition; and PSL in cognitive systems. Applications of PSL included: image and signal processing; multi-modal information processing; sensor/information fusion; human computer interaction; data mining and Web mining; forensic anthropology; and bioinformatics.

General

Imprint:	Springer-Verlag
Country of origin:	Germany
Series:	Lecture Notes in Artificial Intelligence, 7081
Release date:	February 2012
First published:	2012
Editors:	Friedhelm Schwenker • Edmondo Trentin
Dimensions:	235 x 155 x 13mm (L x W x T)
Format:	Paperback
Pages:	159
Edition:	2012
ISBN-13:	978-3-642-28257-7
Categories:	Books > Computing & IT > General theory of computing > Data structures Books > Computing & IT > Computer programming > Algorithms & procedures Books > Computing & IT > Applications of computing > Pattern recognition Books > Science & Mathematics > Biology, life sciences > Life sciences: general issues > General Books > Computing & IT > Applications of computing > Databases > General Books > Computing & IT > Applications of computing > Artificial intelligence > General Books > Computing & IT > Applications of computing > Image processing > General Promotions
LSN:	3-642-28257-1
Barcode:	9783642282577

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