Abstract：Inspired by geometric mean metric learning(GMML), a convex discriminant canonical correlation analysis(CDCA) is proposed. The learning of two projection matrices is transformed into a geodesic convex problem of metric learning. Thereby a closed form solution is acquired and simultaneously discriminant fused features are extracted directly. The experiments on artificial and real datasets verify the effectiveness of CDCA.
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2017, Vol. 30 
