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Labeling Complicated Objects: Multi-View Multi-Instance Multi-Label Learning

Published in Proceedings of the AAAI Conference on Artificial Intelligence • Jun 21, 2014
NobleIDNI7P07W42R14S10
Authors:
Cam-Tu Nguyen
,
Xiaoliang Wang
,
Jing Liu

Abstract

Multi-Instance Multi-Label (MIML) is a learning framework where an example is associated with multiple labels and represented by a set of feature vectors (multiple instances). In the formalization of MIML learning, instances come from a single source (single view). To leverage multiple information s...

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