AI RESEARCH
Hyperbolic Enhanced Representation Learning for Incomplete Multi-view Clustering
arXiv CS.LG
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ArXi:2604.16959v1 Announce Type: new Incomplete Multi-View Clustering (IMVC) faces the challenge of learning discriminative representations from fragmentary observations while maintaining robustness against missing views. However, prevalent Euclidean-based methods suffer from a geometric mismatch when modeling real-world data with intrinsic hierarchies, leading to semantic blurring where representations drift towards spatially proximal but semantically distinct neighbors. To bridge this gap, we propose HERL, a Hyperbolic Enhanced Representation Learning framework for