Discriminative Orthogonal Nonnegative matrix factorization with flexibility for data representation
We propose the Discriminative Orthogonal NMF method for data representation. Our method respects the locally geometrical structure of the data. Our method employs the global discriminant information of the data. We make the method be more adaptive with flexible orthogonality regularization. Extensive experiments suggest the superiority of the proposed method.
nonnegative matrix factorization data representation flexible orthogonality manifold discriminant learning