Researchers have developed a new multi-view clustering framework called PLCI to address challenges posed by imperfect information in real-world datasets. This framework unifies the handling of incomplete views and noisy correspondences by treating cross-view counterparts as latent variables. PLCI integrates instance-level reliability and semantic transport to infer the posterior distribution of these latent counterparts, demonstrating effectiveness across six datasets against ten state-of-the-art methods. AI
RANK_REASON This is a research paper describing a new method for multi-view clustering. [lever_c_demoted from research: ic=1 ai=1.0]
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