Orthogonal Nonnegative Tucker Decomposition

发布时间：2020-09-29 作者：浏览次数：

Speaker:	潘珺珺	DateTime:	2020年10月5日（星期一）19:00--21:00
Brief Introduction to Speaker: 潘珺珺，（比利时）Université de Mons 博士后。		Place:	腾讯会议：861899196
Abstract:In this talk, we study nonnegative tensor data and propose an orthogonal nonnegative Tucker decomposition (ONTD). We discuss some properties of ONTD and develop a convex relaxation algorithm of the augmented Lagrangian function to solve the optimization problem. The convergence of the algorithm is given. We employ ONTD on the image data sets from the real world applications including face recognition, image representation, hyperspectral unmixing. Numerical results are shown to illustrate the effectiveness of the proposed algorithm.