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Spectral regression discriminant analysis (SRDA) is an important subspace learning method. It has a tunable parameter, i.e., the regularization parameter, which critically affects the performance. However, how to set this parameter automatically has not been well solved to date. In SRDA, this regularization parameter was only set as a constant, which is usually suboptimal. In this paper, we develop...
This paper provides a generic framework of component analysis (CA) methods introducing a new expression for scatter matrices and Gram matrices, called Generalized Pairwise Expression (GPE). This expression is quite compact but highly powerful: The framework includes not only (1) the standard CA methods but also (2) several regularization techniques, (3) weighted extensions, (4) some clustering methods,...
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