Sparse Learning Under Regularization Framework: Theory and Applications - Softcover

Yang, Haiqin; King, Irwin; R. Lyu, Michael

 
9783844330304: Sparse Learning Under Regularization Framework: Theory and Applications
Softcover
ISBN 10: 3844330305 ISBN 13: 9783844330304
Verlag: LAP LAMBERT Academic Publishing, 2011

Inhaltsangabe

Regularization is a dominant theme in machine learning and statistics due to its prominent ability in providing an intuitive and principled tool for learning from high-dimensional data. As large-scale learning applications become popular, developing efficient algorithms and parsimonious models become promising and necessary for these applications. Aiming at solving large-scale learning problems, this book tackles the key research problems ranging from feature selection to learning with mixed unlabeled data and learning data similarity representation. More specifically, we focus on the problems in three areas: online learning, semi-supervised learning, and multiple kernel learning. The proposed models can be applied in various applications, including marketing analysis, bioinformatics, pattern recognition, etc.

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Über die Autorin bzw. den Autor

Haiqin Yang finished his Ph.D. study in Computer Science and Engineering, the Chinese University of Hong Kong in 2010. His research interests include machine learning, data mining, financial engineering, pattern recognition, etc. He has conducted various research work in these areas and output many publications and patents.

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Verlag
LAP LAMBERT Academic Publishing
Erscheinungsdatum
2011
Sprache
Englisch
ISBN 10 
3844330305
ISBN 13 
9783844330304
Einband
Taschenbuch
Anzahl der Seiten
152
Kontakt zum Hersteller
Nicht verfügbar
Verantwortliche Person
Fastbook Publishing
customerservice@vdm-vsg.de

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Riga
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