关键词: 显隐视角协同, 多视角学习, 共享隐空间, 模糊系统, 极限学习

Abstract: Multi-view datasets are frequently encountered in learning tasks. However, existing multi-view approaches mainly focus on the visible views and ignore the hidden information shared by the visible views. To address this problem, a multi-view fuzzy system (FS) which utilizes the hidden information shared by the multiple visible views is proposed in this paper. More specifically, using the ridge regression extreme learning fuzzy system (RR-EL-FS) as the base model, an approach with the cooperation of visible and hidden views (RR-EL-FS-CVH) is proposed for multi-view learning. This method can make better use of the effective information of the hidden space than the previous multi-view methods, and thus can further improve the generalization performance of the trained model. Extensive experiments are conducted to validate its effectiveness.

Key words: cooperation between visible and hidden views, multi-view learning, shared hidden space, fuzzy system;extreme learning