| Document Date: 2012-10-02 09:45:02
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City Cambridge / / Company SIAM Journal / MIT Press / / Country Jordan / / / Facility University of Alberta / / Holiday Assumption / / IndustryTerm proximal gradient algorithms / Sparse approximate solutions / iterative shrinkage-thresholding algorithm / low rank solutions / Greedy algorithms / inner product / sparse solution / sparse solutions / vanilla boosting algorithm / local search / local search objective / local search scheme can / neural networks / final algorithm / hybrid algorithm / line search / corrective algorithm / ordinary gradient algorithm / real-world web image database / singular value thresholding algorithm / Approximate solutions / accelerated proximal gradient algorithm / local greedy search / / Organization MIT / Boosting Approach Xinhua Zhang∗ / Yaoliang Yu and Dale Schuurmans Department of Computing Science / University of Alberta / / Person Dale Schuurmans / Ai / / / Product Pentax K-x Digital Camera / / ProgrammingLanguage C / / ProvinceOrState Hawaii / Massachusetts / / PublishedMedium Machine Learning / / Technology singular value thresholding algorithm / accelerated proximal gradient algorithm / Frank-Wolfe algorithm / vanilla boosting algorithm / hybrid algorithm / boosting Algorithm / iterative shrinkage-thresholding algorithm / 2 Algorithm / ordinary gradient algorithm / machine learning / html / proximal gradient algorithms / / URL http /
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Accelerated Training for Matrix-norm Regularization: A Boosting Approach Xinhua Zhang∗, Yaoliang Yu and Dale Schuurmans Department of Computing Science, University of Alberta, Edmonton AB T6G 2E8, Canada {xinhua2,yaoli