Soft Margin Multiple Kernel Learning

Multiple kernel learning (MKL) has been proposed for kernel methods by learning the optimal kernel from a set of predefined base kernels. However, the traditional L 1 MKL method often achieves worse results than the simplest method using the average of base kernels (i.e., average kernel) in some pra...

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Veröffentlicht in:	IEEE transaction on neural networks and learning systems Jg. 24; H. 5; S. 749 - 761
Hauptverfasser:	Xinxing Xu, Tsang, I. W., Dong Xu
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	New York, NY IEEE 01.05.2013 Institute of Electrical and Electronics Engineers The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Schlagworte:	Algorithms Applied sciences Artificial intelligence Computer science; control theory; systems Data processing. List processing. Character string processing Exact sciences and technology Fasteners Hinges Kernel Kernels Learning Learning and adaptive systems Linear programming Mathematical models Memory organisation. Data processing Multiple kernel learning Neural networks Operations research Optimization Pattern recognition. Digital image processing. Computational geometry Recognition Software Studies Support vector machines Training Vectors Multiple kernel learning Action Event detection support vector machines Motion estimation Video signal Modeling Kernel method Loss function Behavioral analysis Efficiency Scene analysis Vector support machine Objective function Learning algorithm Single machine
ISSN:	2162-237X, 2162-2388, 2162-2388
Online-Zugang:	Volltext
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