Abstract: In sparse principal component analysis we are given noisy observations of a low-rank matrix of dimension n × p and seek to reconstruct it under additional sparsity assumptions. In particular, we as...
Publication Year: 2016
Publication Date: 2016-01-01
Language: en
Type: article
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Cited By Count: 9
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