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Multi-view multi-instance multi-label learning based on collaborative matrix factorization
conference contribution
posted on 2019-01-01, 00:00 authored by Yuying Xing, Guoxian Yu, Carlotta Domeniconi, Jun Wang, Zili ZhangZili Zhang, Maozu GuoMulti-view Multi-instance Multi-label Learning(M3L) deals with complex objects encompassing diverse instances, represented with different feature views, and annotated with multiple labels. Existing M3L solutions only partially explore the inter or intra relations between objects (or bags), instances, and labels, which can convey important contextual information for M3L. As such, they may have a compromised performance. In this paper, we propose a collaborative matrix factorization based solution called M3Lcmf. M3Lcmf first uses a heterogeneous network composed of nodes of bags, instances, and labels, to encode different types of relations via multiple relational data matrices. To preserve the intrinsic structure of the data matrices, M3Lcmf collaboratively factorizes them into low-rank matrices, explores the latent relationships between bags, instances, and labels, and selectively merges the data matrices. An aggregation scheme is further introduced to aggregate the instance-level labels into bag-level and to guide the factorization. An empirical study on benchmark datasets show that M3Lcmf outperforms other related competitive solutions both in the instance-level and bag-level prediction.
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AAAI Artificial Intelligence, Innovative Applications of Artificial Intelligence, Educational Advances in Artificial Intelligence. Conferences & Symposium (33rd, 31st, 9th : 2019 : Honolulu, Hawaii)Pagination
5508 - 5515Publisher
Association for the Advancement of Artificial IntelligenceLocation
Honolulu, HawaiiPlace of publication
[Honolulu, Hawaii]Start date
2019-01-27End date
2019-02-01Language
engPublication classification
E1 Full written paper - refereedCopyright notice
[2019, Association for the Advancement of Artificial Intelligence]Editor/Contributor(s)
[Unknown]Title of proceedings
AAAI-19, IAAI-19, EAAI-19 : Proceedings of the 33rd Conference on Artificial Intelligence, 31st Conference on Innovative Applications of Artificial Intelligence & the 9th Symposium on Educational Advances in Artificial IntelligenceUsage metrics
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