2013
NeurIPS
NeurIPS 2013
Stochastic Optimization of PCA with Capped MSG
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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- Artificial Intelligence and Mathematics & Optimization
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- Stochastic Methods
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Authors
Topics
Machine Learning > Core Methods > Representation Learning
Machine Learning > Optimization & Theory > Optimization
Mathematics & Optimization > Optimization > Stochastic Methods
Machine Learning > Core Methods > Dimensionality Reduction
Machine Learning > Optimization & Theory > Stochastic Methods
Deep Learning > Optimization & Theory > Stochastic Methods