Gradient-based Sparse Principal Component Analysis with Extensions to Online Learning

19 Nov 2019Yixuan QiuJing LeiKathryn Roeder

Sparse principal component analysis (PCA) is an important technique for dimensionality reduction of high-dimensional data. However, most existing sparse PCA algorithms are based on non-convex optimization, which provide little guarantee on the global convergence... (read more)

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