Sparse Learning Under Regularization Framework: Theory and Applications - Couverture souple

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

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

Synopsis

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.

Les informations fournies dans la section « Synopsis » peuvent faire référence à une autre édition de ce titre.

Présentation de l'éditeur

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.

Biographie de l'auteur

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.

Les informations fournies dans la section « A propos du livre » peuvent faire référence à une autre édition de ce titre.

Éditeur
LAP LAMBERT Academic Publishing
Date d'édition
2011
Langue
anglais
ISBN 10 
3844330305
ISBN 13 
9783844330304
Reliure
Broché
Nombre de pages
152
Coordonnées du fabricant
non disponible
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