ANIMC: A Soft Framework for Auto-weighted Noisy and Incomplete Multi-view Clustering 事件

ANIMC: A Soft Framework for Auto-weighted Noisy and Incomplete Multi-view Clustering arXiv:2011.10331v4 Announce Type: replace Abstract: Multi-view clustering has wide applications in many image processing scenarios. In these scenarios, original image data often contain missing instances and noises, which is ignored by most multi-view clustering methods. However, missing instances may make these methods difficult to use directly and noises will lead to unreliable clustering results. In this pap