Equilibrium K-Means (EKM) is a novel fuzzy clustering algorithm that is robust to imbalanced data by preventing centroids from crowding together in the center of large clusters.
CDIMC-net is a novel deep clustering network that effectively handles incomplete multi-view data by incorporating view-specific deep encoders, graph embedding, and a self-paced learning strategy to capture high-level features, preserve local structure, and reduce the negative influence of outliers.