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Regularization-Based Multitask Learning With Applications to Genome Biology and Biological Imaging

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Text/Journal Article
Datum
2014
Autor:innen
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Quelle
KI - Künstliche Intelligenz: Vol. 28, No. 1
Verlag
Springer
Zusammenfassung
The aim of multitask learning is to improve the generalization performance of a set of related tasks by exploiting complementary information about the tasks. In this paper, we review established approaches for regularization based multitask learning, sketch some recent developments, and demonstrate their applications in Computational Biology and Biological Imaging.
Beschreibung
Widmer, Christian; Kloft, Marius; Lou, Xinghua; Rätsch, Gunnar (2014): Regularization-Based Multitask Learning With Applications to Genome Biology and Biological Imaging. KI - Künstliche Intelligenz: Vol. 28, No. 1. Springer. PISSN: 1610-1987. pp. 29-33
Schlagwörter
Multitask learning , Regularized risk minimization , Transfer learning
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Künstliche Intelligenz 28(1) - März 2014