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Least squares
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#	Item
761	Approximate Generalized Inverse Preconditioning Methods for Least Squares Problems Xiaoke Cui DOCTOR OF Add to Reading List Source URL: www.nii.ac.jp Language: English - Date: 2010-03-08 19:45:47 Regression analysis Statistics Preconditioner Least squares Iterative method Linear least squares Generalized minimal residual method Matrix Mathematical optimization Numerical linear algebra Numerical analysis Mathematics
762	Regularized Regression David M. Blei Columbia University December 3, 2014 Modern regression problems are high dimensional, which means that the number of covariates p is large. In practice statisticians regularize their Add to Reading List Source URL: www.cs.columbia.edu Language: English - Date: 2015-03-12 00:16:19 Econometrics Least squares Parametric statistics Regularization Linear regression Tikhonov regularization Elastic net regularization Mean squared error Maximum likelihood Statistics Estimation theory Regression analysis
763	24551 Quantile Regression – A Statisticians Approach to the Local Ice PressureArea Relationship Tom Morrison and Paul Spencer, Ausenco, Calgary, Alberta, CANADA Copyright 2014, Offshore Technology Conference This paper Add to Reading List Source URL: www.ausenco.com Language: English - Date: 2014-03-12 20:42:25 Quantile Linear regression Simple linear regression Power law Normal distribution Standard error Least squares Confidence band Median Statistics Regression analysis Quantile regression
764	arXiv:1202.0515v3 [stat.ML] 21 AugHigh-Dimensional Feature Selection by Feature-Wise Kernelized Lasso Makoto Yamada1 , Wittawat Jitkrittum2 , Leonid Sigal3 , Eric P. Xing4 , and Masashi Sugiyama2 1 Yahoo! Labs, 70 Add to Reading List Source URL: labs.yahoo.com Language: English - Date: 2014-02-26 18:29:12 Non-parametric statistics Dimension reduction Feature selection Model selection Kernel trick Lasso Kernel density estimation Supervised learning Least squares Statistics Regression analysis Machine learning
765	Ad Click Prediction: a View from the Trenches H. Brendan McMahan, Gary Holt, D. Sculley, Michael Young, Dietmar Ebner, Julian Grady, Lan Nie, Todd Phillips, Eugene Davydov, Daniel Golovin, Sharat Chikkerur, Dan Liu, Mart Add to Reading List Source URL: static.googleusercontent.com Language: English - Date: 2013-08-12 13:25:40 Cross-validation Poisson regression Pattern recognition Feature selection Least squares Regression analysis Regularization Gradient boosting Book:Machine Learning - The Complete Guide Statistics Machine learning Supervised learning
766	Merging in situ and satellite data for gridded multidecadal analyses of sea surface temperature fields Summary Many climate-related applications require fully interpolated (i.e., with no spatial or temporal gaps) gridded Add to Reading List Source URL: www.earthtemp.net Language: English - Date: 2015-01-22 16:12:57 Regression analysis Interpolation Kriging Multivariate interpolation Sea surface temperature Variance Least squares Statistics Oceanography Geostatistics
767	syllabus_PHS_552_Spring2012 Add to Reading List Source URL: pophealth.wisc.edu Language: English - Date: 2012-10-17 10:25:20 Logistic regression Proportional hazards models Regression Coefficient of determination Least squares Separation Predictive analytics Statistics Regression analysis Linear regression
768	Max-margin Methods Notation Notation Example images (v1T, v2T,…,v5T)T, where Add to Reading List Source URL: users.cecs.anu.edu.au Language: English - Date: 2009-06-21 14:47:09 Machine learning Support vector machines Information theory Differential geometry Least squares support vector machine Statistics Statistical classification Hinge loss
769	doi:S1573 Add to Reading List Source URL: siteresources.worldbank.org Language: English - Date: 2008-04-23 09:26:28 Econometrics Evaluation methods Estimation theory Parametric statistics Impact evaluation Randomized controlled trial Instrumental variable Counterfactual conditional Ordinary least squares Statistics Science Regression analysis
770	Coal Seam Thickness Prediction based on Least Squares Support Vector Machines and Kriging Method Chen Youkuo School of Resource and Earth Science, Key Laboratory of CBM Resources and Reservoir Formation Process of Minist Add to Reading List Source URL: www.ejge.com Language: English - Date: 2015-01-03 20:12:27 Regression analysis Multivariate interpolation Statistical classification Variogram Kriging Least squares support vector machine Support vector machine Linear interpolation Linear regression Statistics Geostatistics Interpolation

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