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Generalized Power Method for Sparse Principal Component Analysis

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Figure

Table 1: Theoretical upper-bounds on the sparsity parameters γ.
Table 2: New algorithms for sparse PCA.
Table 3: Sparse PCA algorithms we compare in this section.
Table 4: Details on the random and fixed choices of the sparsity-inducing parameters γ1 and γ2leading to the results displayed in Table 5
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