Generalized multiview regression for feature extraction

Zhihui Lai, Yiling Lin, Jiacan Zheng, Jie Zhou, Heng Kong

Abstract: Highlights•A multiview method, GMR, is proposed for feature extraction, which considers view consistency and complementary information simultaneously.•GMR explores the complementary properties using view-specific geometric structure and achieves the view consistency using label information.•The L2,1 norm is imposed on objective function and regularization term to eliminate redundant information so as to extract robust features.•An iterative algorithm is presented to obtain the local optimal solution, and the convergence and computational complexity are given.•Extensive experiments are conducted on several well-known datasets to illustrate the competitive performance of the GMR.