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Traditional bidirectional two-dimension (2D) principal component analysis ((2D)PCA-L2) is sensitive to outliers because its objective function is the least squares criterion based on L2-norm. This(More)
Traditional bidirectional two-dimension (2D) principal component analysis ((2D)PCA-L2) is sensitive to outliers because its objective function is the least squares criterion based on L2-norm. This(More)