Self-Learning Symmetric Multi-view Probabilistic Clustering. (arXiv:2305.07307v1 [cs.CV])

Multi-view Clustering (MVC) has achieved significant progress, with many
efforts dedicated to learn knowledge from multiple views. However, most
existing methods are either not applicable or require additional steps for
incomplete multi-view clustering. Such a limitation results in poor-quality
clustering performance and poor missing view adaptation. Besides, noise or
outliers might significantly degrade the overall clustering performance, which
are not handled well by most existing methods. Moreover, category information
is required in most existing methods, which severely affects the clustering …

arxiv clustering knowledge learn multiple noise outliers performance progress quality self-learning