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Stochastic Optimization of PCA with Capped MSG
Published 5 Jul 2013 in stat.ML and cs.LG | (1307.1674v1)
Abstract: We study PCA as a stochastic optimization problem and propose a novel stochastic approximation algorithm which we refer to as "Matrix Stochastic Gradient" (MSG), as well as a practical variant, Capped MSG. We study the method both theoretically and empirically.
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