Incomplete Multiview Clustering via Low-Rank Tensor Ring Completion

Figure 1

The suggested IMC method’s framework. For the given multiview data with missing instances, the constructed similarity graphs is incomplete such that fails to provide the complementary information for a good consensus clustering indicator learning . To restore the missing information, the tensor ring decomposition is applied to learn a complete tensor representation from the incomplete tensor generated by stacking incomplete graphs into a 3^rd-order tensor. In this way, the complete graphs can be restored and then be fused for learning a consensus clustering indicator . Because each viewpoint’s contributions vary, the consensus clustering indicator learning process makes use of the adaptive weighting technique.