Multiple instance classification via quadratic programming

Multiple instance learning (MIL) is a variation of supervised learning, where data consists of labeled bags and each bag contains a set of instances. Unlike traditional supervised learning, labels are not known for the instances in MIL. Existing approaches in the literature make use of certain assum...

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Veröffentlicht in:	Journal of global optimization Jg. 83; H. 4; S. 639 - 670
Hauptverfasser:	Küçükaşcı, Emel Şeyma, Baydoğan, Mustafa Gökçe, Taşkın, Z. Caner
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	New York Springer US 01.08.2022 Springer Springer Nature B.V
Schlagworte:	Algorithms Classification Computer Science Heuristic methods Labels Mathematical optimization Mathematics Mathematics and Statistics Mixed integer Operations Research/Decision Theory Optimization Quadratic programming Real Functions Supervised learning Quadratic programming Multiple instance learning Classification
ISSN:	0925-5001, 1573-2916
Online-Zugang:	Volltext
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