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Multi-instance multi-label active learning

Published • Jul 28, 2017
NobleIDNI7P98W44R84S93
Authors:
Sheng-Jun Huang
,
Nengneng Gao
,
Songcan Chen

Abstract

Multi-instance multi-label learning(MIML) has been successfully applied into many real-world applications. Along with the enhancing of the expressive power, the cost of labelling a MIML example increases significantly. And thus it becomes an important task to train an effective MIML model with as fe...

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