| Document Date: 2013-05-09 18:59:22
Open Document File Size: 443,42 KBShare Result on Facebook
City Gaussian / Atlanta / Asuncion / Leverage / Boston / Linn / / Company SIAM Journal / Neural Information Processing Systems / MIT Press / Dexter / The times / / Country United States / / / Facility Stanford University / / IndustryTerm downstream applications / randomized matrix algorithms / projection algorithms / approximation algorithm / data analysis applications / leverage score approximation algorithm / machine learning applications / realistic applications / random projection algorithms / learning applications / / Organization MIT / Stanford University / / Person Newman / Norm Bounds / Alex Gittens / / Position author / Prime Minister / general data analysis applications / D. J. / / Product k+ 8 / / ProvinceOrState South Carolina / Georgia / / PublishedMedium Machine Learning / Journal of Machine Learning Research / PLoS Genetics / / SportsLeague Stanford University / / Technology M. W. Randomized algorithms / Genomics / randomized matrix algorithms / random projection algorithms / approximation algorithm / gene expression / machine learning / Simulation / Leverage Score Approximation Algorithms / leverage score approximation algorithm / projection algorithms / / URL http /
SocialTag |
Revisiting the Nystr¨ om method for improved large-scale machine learning Alex Gittens Dept. of Applied and Computational Math, CalTech, Pasadena CAUSA