En-Ze Ji

Content-style Disentanglement Guided Representation Learning for Deep Incomplete Multi-view Clustering

A content-style disentanglement guided representation learning is proposed for the incomplete multi-view clustering (CSMVC), which designs a view-specific dual-representation learning architecture that extracts view-invariant content representations and view-specific style representations from self-supervised reconstru...

Single-phase incomplete multi-view clustering via joint anchor refactoring and tensorial bipartite graph learning.

This work proposes a Single-phase Incomplete Multi-view Clustering via Joint Anchor Refactoring and Tensorial Bipartite Graph (SIMC-ARTB), a novel unified framework that jointly integrates anchor refactoring, aligned graph fusion, and single-phase label learning.

Decomposed tensorized graph learning with representation-induced view recovery for federated incomplete multi-view clustering