Separable Consistency and Diversity Feature Learning for Multi-View Clustering
Author:
Affiliation:
1. College of Electronic and Information Engineering, Southwest University, Chongqing, China
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Link
http://xplorestaging.ieee.org/ielx8/97/10380231/10545549.pdf?arnumber=10545549
Reference39 articles.
1. Multi-view clustering on unmapped data via constrained non-negative matrix factorization
2. Robust multi-view non-negative matrix factorization with adaptive graph and diversity constraints
3. Multi-view clustering via multi-manifold regularized non-negative matrix factorization
4. Centric graph regularized log-norm sparse non-negative matrix factorization for multi-view clustering
5. Measuring Diversity in Graph Learning: A Unified Framework for Structured Multi-view Clustering
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