Poster
Stochastic Optimization of PCA with Capped MSG
Raman Arora · Andrew Cotter · Nati Srebro
Harrah's Special Events Center, 2nd Floor
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Abstract
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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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