Beyond Missing Rates: Rethinking Incomplete Multi-View Clustering with Protocol Divergence
Incomplete multi-view clustering (IMVC) is typically evaluated by retraining separate models under different missing-view configurations. Evaluations indexed only by nominal missing rate can overlook differences in observation structure across missing-view protocols. We show that missing-data protocols with identical nominal missing rates can induce substantially different learning regimes, differing by approximately 50-fold in the proportion of fully observed samples. We formalize this phenomenon as protocol divergence, which quantifies structural disparities among missing-view protocols beyond marginal missing rates. Furthermore, we analyze support-gated reconstruction mechanisms and sh...
| Authors | Haolu Liu, Xiyue Wang, Xuanting Xie et al. |
|---|---|
| Primary category | cs.LG |
| Published | 3 June 2026 |
| Last updated at source | 29 September 2026 |
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