2016
ICML
ICML 2016
Solving Ridge Regression using Sketched Preconditioned SVRG
Abstract
We develop a novel preconditioning method for ridge regression, based on recent linear sketching methods. By equipping Stochastic Variance Reduced Gradient (SVRG) with this preconditioning process, we obtain a significant speed-up relative to fast stochastic methods such as SVRG, SDCA and SAG.
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Interdisciplinary Bridge
- Machine Learning and Mathematics & Optimization
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Keyword Pioneer
- numerical optimization
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Cross-Pollinator
- Artificial Intelligence, Machine Learning, Mathematics & Optimization, Natural Language Processing
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Trend Setter
- Numerical Analysis
Authors
Topics
Machine Learning > Core Methods > Regression
Machine Learning > Optimization & Theory > Neural Network Optimization
Machine Learning > Optimization & Theory > Optimization
Mathematics & Optimization > Mathematics > Numerical Analysis
Mathematics & Optimization > Optimization > Continuous Optimization