Consensus and complementarity based maximum entropy discrimination for multi-view classification

Maximum entropy discrimination (MED) is a general framework for discriminative estimation based on the maximum entropy and large margin principles, but it just uses only one view of the data not all the views of the data. Although Multi-view maximum entropy discrimination considered the multi-view i...

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Veröffentlicht in:	Information sciences 2016-11, Vol.367-368, p.296-310
Hauptverfasser:	Chao, Guoqing, Sun, Shiliang
Format:	Artikel
Sprache:	eng
Schlagworte:	Classification Discrimination Kernel method Large-margin Learning Maximum entropy Maximum entropy discrimination Multi-view learning Optimization Subspaces Support vector machines
Online-Zugang:	Volltext
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