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...
Finding related papers...
Discussions
(0)No comments yet
Be the first to share your thoughts!