ANIMC: A Soft Framework for Auto-weighted Noisy and Incomplete Multi-view Clustering
Published in
arXiv.org(2020)External Links:
TL
TL;DR
A novel Auto-weighted Noisy and Incomplete Multi-view Clustering framework (ANIMC) via a soft auto-weighting strategy and a doubly soft regular regression model is proposed, which has three unique advantages: it is a soft algorithm to adjust the framework in different scenarios, thereby improving its generalization ability.