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Block principal component analysis with $\boldsymbol {\ell _{1}}$ -norm (BPCA-L1) has demonstrated its effectiveness in a lot of visual classification and data mining tasks. However, the greedy strategy for solving the $\boldsymbol {\ell _{1}}$ -norm maximization problem is prone to being struck in local solutions. In this paper, we propose a BPCA with nongreedy $\boldsymbol {\ell _{1}}$ -norm...
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