Low-Rank Approximation of Data Matrices Using Robust Sparse Principal Component Analysis
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Publisher
Springer Nature Switzerland
Link
https://link.springer.com/content/pdf/10.1007/978-3-031-65993-5_44
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5. Croux, C., Ollila, E., Oja, H.: Sign and rank covariance matrices: statistical properties and application to principal components analysis. In: Dodge, Y. (ed.) Statistical Data Analysis Based on the L1-Norm and Related Methods, pp. 257–269. Birkhäuser Basel, Basel (2002)
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