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Contrastive Label Enhancement
Label distribution learning (LDL) is a new machine learning paradigm for solving label ambiguity.
Multi-view Semantic Consistency based Information Bottleneck for Clustering
In this way, the learned semantic consistency from multi-view data can improve the information bottleneck to more exactly distinguish the consistent information and learn a unified feature representation with more discriminative consistent information for clustering.
MCoCo: Multi-level Consistency Collaborative Multi-view Clustering
Further, we designed a multi-level consistency collaboration strategy, which utilizes the consistent information of semantic space as a self-supervised signal to collaborate with the cluster assignments in feature space.
Ranked #1 on
Multiview Clustering
on Fashion-MNIST
