Flexible Clustered Multi-Task Learning by Learning Representative Tasks

Multi-task learning (MTL) methods have shown promising performance by learning multiple relevant tasks simultaneously, which exploits to share useful information across relevant tasks. Among various MTL methods, clustered multi-task learning (CMTL) assumes that all tasks can be clustered into groups...

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Veröffentlicht in:	IEEE transactions on pattern analysis and machine intelligence Jg. 38; H. 2; S. 266 - 278
Hauptverfasser:	Zhou, Qiang, Zhao, Qi
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	United States IEEE 01.02.2016
Schlagworte:	Clustered Multi-Task Learning Covariance matrices Group Sparsity Kernel Learning systems Optimization Representative Task Robustness Training data Visualization representative task group sparsity Clustered multi-task learning
ISSN:	0162-8828, 1939-3539, 2160-9292, 1939-3539
Online-Zugang:	Volltext
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