Double Self-weighted Multi-view Clustering via Adaptive View Fusion 事件

Double Self-weighted Multi-view Clustering via Adaptive View Fusion arXiv:2011.10396v3 Announce Type: replace-cross Abstract: Multi-view clustering has been applied in many real-world applications where original data often contain noises. Some graph-based multi-view clustering methods have been proposed to try to reduce the negative influence of noises. However, previous graph-based multi-view clustering methods treat all features equally even if there are redundant features or noises, which is