Optimal Mean Robust Principal Component Analysis
Pages: 1062 - 1070
Published: Jun 21, 2014
Abstract
Principal Component Analysis (PCA) is the most widely used unsupervised dimensionality reduction approach. In recent research, several robust PCA algorithms were presented to enhance the robustness of PCA model. However, the existing robust PCA methods incorrectly center the data using the l2-norm distance to calculate the mean, which actually is not the optimal mean due to the l1-norm used in the objective functions. In this paper, we propose...
Paper Details
Title
Optimal Mean Robust Principal Component Analysis
Published Date
Jun 21, 2014
Pages
1062 - 1070
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