Avoiding Optimal Mean ℓ 2,1 -Norm Maximization-Based Robust PCA for Reconstruction

Robust principal component analysis (PCA) is one of the most important dimension-reduction techniques for handling high-dimensional data with outliers. However, most of the existing robust PCA presupposes that the mean of the data is zero and incorrectly utilizes the average of data as the optimal mean of robust PCA. In fact, this assumption holds only for the squared -norm-based traditional PCA. ...