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In this paper we derive an algorithm to follow the entire solution path of the sparse principal component analysis (PCA) problem. The core idea is to iteratively identify the pairwise variables along which the objective function of the sparse PCA model can be largely increased, and then incrementally update the coefficients of the two variables so selected by a small stepsize. The new algorithm dominates...
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