Algorithm-Dependent Generalization Bounds for Multi-Task Learning

Often, tasks are collected for multi-task learning (MTL) because they share similar feature structures. Based on this observation, in this paper, we present novel algorithm-dependent generalization bounds for MTL by exploiting the notion of algorithmic stability. We focus on the performance of one p...

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Bibliographische Detailangaben

Veröffentlicht in:	IEEE transactions on pattern analysis and machine intelligence. - 1979. - 39(2017), 2 vom: 01. Feb., Seite 227-241
1. Verfasser:	Liu, Tongliang (VerfasserIn)
Weitere Verfasser:	Tao, Dacheng, Song, Mingli, Maybank, Stephen J
Format:	Online-Aufsatz
Sprache:	English
Veröffentlicht:	2017
Zugriff auf das übergeordnete Werk:	IEEE transactions on pattern analysis and machine intelligence
Schlagworte:	Journal Article Research Support, Non-U.S. Gov't