A missing-pattern tree groups data by missing patterns for per-group clustering, followed by uncertainty-weighted ensemble and knowledge distillation to better exploit available pairs in incomplete multi-view clustering.
Semantic invariant multi-view cluster- ing with fully incomplete information.IEEE Transactions on Pattern Analysis and Machine Intelligence, 46(4):2139–2150,
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Missing Pattern Tree based Decision Grouping and Ensemble for Enhancing Pair Utilization in Deep Incomplete Multi-View Clustering
A missing-pattern tree groups data by missing patterns for per-group clustering, followed by uncertainty-weighted ensemble and knowledge distillation to better exploit available pairs in incomplete multi-view clustering.