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Instance Annotation for Multi-Instance Multi-Label Learning

Published in ACM Transactions on Knowledge Discovery from Data • Sep 1, 2013
NobleIDNI8P75W24R96S15
Authors:
Forrest Briggs
,
Xiaoli Z. Fern
,
Raviv Raich

Abstract

Multi-instance multi-label learning (MIML) is a framework for supervised classification where the objects to be classified are bags of instances associated with multiple labels. For example, an image can be represented as a bag of segments and associated with a list of objects it contains. Prior wor...

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