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Integration of Single-view Graphs with Diffusion of Tensor Product Graphs for Multi-view Spectral Clustering
2015
Asian Conference on Machine Learning
Multi-view clustering takes diversity of multiple views (representations) into consideration. Multiple views may be obtained from various sources or different feature subsets and often provide complementary information to each other. In this paper, we propose a novel graph-based approach to integrate multiple representations to improve clustering performance. While original graphs have been widely used in many existing multi-view clustering approaches, the key idea of our approach is to
dblp:conf/acml/ShuL15
fatcat:fmvihjfeezb2bmguxrz7u25p3m