Generalized Principal Component Analysis

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Generalized Principal Component AnalysisThis book provides a comprehensive introduction to the latest advances in the mathematical theory and computational tools for modeling high dimensional data drawn from one or multiple low dimensional subspaces (or manifolds) and potentially corrupted by noise, gross errors, or outliers. This challenging task requires the development of new algebraic, geometric, statistical, and computational methods for efficient and robust estimation and segmentation

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