A Bias Trick for Centered Robust Principal Component Analysis

He, Baokun, Wan, Guihong, Schweitzer, Haim

arXiv.org Machine Learning 

Outlier based Robust Principal Component Analysis (RPCA) requires centering of the non-outliers. We show a "bias trick" that automatically centers these non-outliers. Using this bias trick we obtain the first RPCA algorithm that is optimal with respect to centering.

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