21![A Block Coordinate Gradient Descent Method for Regularized Convex Separable Optimization and Covariance Selection Sangwoon Yun Computational Sciences Korea Institute for Advanced Study A Block Coordinate Gradient Descent Method for Regularized Convex Separable Optimization and Covariance Selection Sangwoon Yun Computational Sciences Korea Institute for Advanced Study](https://www.pdfsearch.io/img/b75a2c3ad8f7f8bbebae837f8b17f062.jpg) | Add to Reading ListSource URL: newton.kias.re.krLanguage: English - Date: 2013-01-31 02:01:01
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22![Bounded Coordinate-Descent for Biological Sequence Classification in High Dimensional Predictor Space Georgiana Ifrim Carsten Wiuf Bounded Coordinate-Descent for Biological Sequence Classification in High Dimensional Predictor Space Georgiana Ifrim Carsten Wiuf](https://www.pdfsearch.io/img/4491fdc7c87cc1a5d22a19129a30405e.jpg) | Add to Reading ListSource URL: www.math.ku.dkLanguage: English - Date: 2012-01-27 08:04:28
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23![Perceptron Learning with Random Coordinate Descent Ling Li Learning Systems Group, California Institute of Technology Abstract. A perceptron is a linear threshold classifier that separates examples with a hyperplane. It Perceptron Learning with Random Coordinate Descent Ling Li Learning Systems Group, California Institute of Technology Abstract. A perceptron is a linear threshold classifier that separates examples with a hyperplane. It](https://www.pdfsearch.io/img/9fe63e76ffb90fffa6ac5e49a57dd7fa.jpg) | Add to Reading ListSource URL: www.work.caltech.eduLanguage: English - Date: 2006-04-22 18:28:41
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24![Errata for Learning output kernels with block coordinate descent Differently from what claimed in Lemma 4.1 of [1], the update for L does not preserve symmetry. However, this doesn’t compromise the validity of Algorit Errata for Learning output kernels with block coordinate descent Differently from what claimed in Lemma 4.1 of [1], the update for L does not preserve symmetry. However, this doesn’t compromise the validity of Algorit](https://www.pdfsearch.io/img/ad667f68c97f8fe5cee68e42ed65133b.jpg) | Add to Reading ListSource URL: people.tuebingen.mpg.deLanguage: English - Date: 2011-07-26 04:13:11
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25![MITSUBISHI ELECTRIC RESEARCH LABORATORIES http://www.merl.com Coordinate Descent for Mixed-norm NMF Potluru, V.K.; LeRoux, J.; Pearlmutter, B.A.; Hershey, J.R.; Brand, M.E. MITSUBISHI ELECTRIC RESEARCH LABORATORIES http://www.merl.com Coordinate Descent for Mixed-norm NMF Potluru, V.K.; LeRoux, J.; Pearlmutter, B.A.; Hershey, J.R.; Brand, M.E.](https://www.pdfsearch.io/img/4aca810d2a4af5cd4c75cc1c8443abed.jpg) | Add to Reading ListSource URL: www.merl.comLanguage: English - Date: 2014-02-21 15:37:21
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26![mS2GD: Mini-Batch Semi-Stochastic Gradient Descent in the Proximal Setting Jie Liu Lehigh University Bethlehem, PA 18015 mS2GD: Mini-Batch Semi-Stochastic Gradient Descent in the Proximal Setting Jie Liu Lehigh University Bethlehem, PA 18015](https://www.pdfsearch.io/img/7e12207aeb326b0f721e64f63384df1b.jpg) | Add to Reading ListSource URL: www.opt-ml.orgLanguage: English - Date: 2014-12-10 11:28:41
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27![S2CD: Semi-Stochastic Coordinate Descent Jakub Koneˇcn´y University of Edinburgh United Kingdom, EH9 3FD [removed] S2CD: Semi-Stochastic Coordinate Descent Jakub Koneˇcn´y University of Edinburgh United Kingdom, EH9 3FD [removed]](https://www.pdfsearch.io/img/1f9b6690b9a51ebfafb5917f2196e6cc.jpg) | Add to Reading ListSource URL: www.opt-ml.orgLanguage: English - Date: 2014-12-10 11:28:33
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28![Coordinate descent converges faster with the Gauss-Southwell rule than random selection Michael Friedlander Department of Mathematics University of California, Davis Coordinate descent converges faster with the Gauss-Southwell rule than random selection Michael Friedlander Department of Mathematics University of California, Davis](https://www.pdfsearch.io/img/4c030e17f295e7539204405d21ef3be9.jpg) | Add to Reading ListSource URL: www.opt-ml.orgLanguage: English - Date: 2014-12-10 11:28:45
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29![Generic Methods for Optimization-Based Modeling Justin Domke Rochester Institute of Technology Abstract Generic Methods for Optimization-Based Modeling Justin Domke Rochester Institute of Technology Abstract](https://www.pdfsearch.io/img/6bc94cfcfccf660821120c766d20ea07.jpg) | Add to Reading ListSource URL: users.cecs.anu.edu.auLanguage: English - Date: 2012-05-24 15:13:47
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30![Randomized Subspace Descent Rafael M. Frongillo Harvard University [removed] Randomized Subspace Descent Rafael M. Frongillo Harvard University [removed]](https://www.pdfsearch.io/img/7ec5d026ce99d9e87f2531a6ad57045d.jpg) | Add to Reading ListSource URL: www.opt-ml.orgLanguage: English - Date: 2014-12-10 11:28:44
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