Abstract
In this paper, we transform the classical linear discriminant analysis (LDA) into a smooth difference-of-convex optimization problem. Then, a new difference-of-convex algorithm with extrapolation is introduced and the convergence of the algorithm is established. Finally, for a face recognition problem, the proposed algorithm achieves better classification performance compared with several current algorithms in the literature.
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