Fast large scale Gaussian process regression using approximate matrix-vector products Vikas Chandrakant Raykar and Ramani Duraiswami {vikas,ramani Department of Computer Science University of Maryland, Co - Matrix function - Document - PDFSEARCH.IO

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	Fast large scale Gaussian process regression using approximate matrix-vector products Vikas Chandrakant Raykar and Ramani Duraiswami {vikas,ramani}@umiacs.umd.edu Department of Computer Science University of Maryland, Co Add to Reading List Document Date: 2007-03-21 08:47:48 Open Document File Size: 1,27 MB Share Result on Facebook Company MIT Press / / / Facility Computer Science University of Maryland / / IndustryTerm process regression using approximate matrix-vector products / / Organization MIT / University of Maryland / Univ. of Maryland / / ProvinceOrState Maryland / / PublishedMedium Machine Learning / / Technology Machine Learning / / SocialTag Gaussian process Covariance function Regression analysis Kriging Gaussian function Gaussian adaptation Statistics Geostatistics Econometrics

Fast large scale Gaussian process regression using approximate matrix-vector products Vikas Chandrakant Raykar and Ramani Duraiswami {vikas,ramani}@umiacs.umd.edu Department of Computer Science University of Maryland, CoAdd to Reading List