Orthogonal Nonnegative Tucker Decomposition
نویسندگان
چکیده
In this paper, we study nonnegative tensor data and propose an orthogonal Tucker decomposition (ONTD). We discuss some properties of ONTD develop a convex relaxation algorithm the augmented Lagrangian function to solve optimization problem. The convergence is given. employ on image sets from real world applications including face recognition, representation, hyperspectral unmixing. Numerical results are shown illustrate effectiveness proposed algorithm.
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ژورنال
عنوان ژورنال: SIAM Journal on Scientific Computing
سال: 2021
ISSN: ['1095-7197', '1064-8275']
DOI: https://doi.org/10.1137/19m1294708