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

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Text/Journal Article

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Datum

2014

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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