Grace Wahba

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Chong GuProfessor of Statistics, Purdue University確認したメールアドレス: stat.purdue.edu
Michael T. HeathProfessor of Computer Science, University of Illinois at Urbana-Champaign確認したメールアドレス: illinois.edu
NASHED, M. Z.Professor of Mathematics, UCF確認したメールアドレス: mail.ucf.edu
Chenlei Leng (冷琛雷)Professor of Statistics, University of Warwick確認したメールアドレス: warwick.ac.uk
Stephen WrightDepartment of Computer Sciences and Wisconsin Institute for Discovery, University of Wisconsin確認したメールアドレス: cs.wisc.edu
Michael FerrisComputer Sciences Dept. and WI. Inst. for Discovery, University of Wisconsin-Madison確認したメールアドレス: cs.wisc.edu
Sunduz KelesProfessor of Statistics and Biostatistics, University of Wisconsin確認したメールアドレス: stat.wisc.edu
Steve AckermanProfessor of Atmospheric and Oceanic Sciences, University of Wisconsin-Madison確認したメールアドレス: ssec.wisc.edu
meyerandUniversity of Wisconsin-Madison確認したメールアドレス: wisc.edu
Hector Corrada BravoAssociate Professor of Computer Science, University of Maryland確認したメールアドレス: umiacs.umd.edu
Ming YuanColumbia University確認したメールアドレス: columbia.edu
Andrew L AlexanderUniversity of Wisconsin確認したメールアドレス: wisc.edu
Sijian WangRutgers University確認したメールアドレス: rutgers.edu
Kevin H. EngEikon Therapeutics確認したメールアドレス: eikontx.com
Peter J. Basser, Ph.D.Senior Investigator, NICHD, NIH確認したメールアドレス: helix.nih.gov
Moo K. ChungUniversity of Wisconsin-Madison確認したメールアドレス: wisc.edu
Nancy HeckmanProfessor of Statistics, University of British Columbia確認したメールアドレス: stat.ubc.ca
Richard J DavidsonUniversity of Wisconsin - Madison確認したメールアドレス: wisc.edu
Xiaojin ZhuProfessor in Computer Science at University of Wisconsin-Madison確認したメールアドレス: cs.wisc.edu
Menggang YuUniversity of Wisconsion, Madison確認したメールアドレス: biostat.wisc.edu

フォロー

Grace Wahba

Professor of Statistics, University of Wisconsin-Madison

確認したメールアドレス: stat.wisc.edu - ホームページ

Machine Learning Statistical Model Building


タイトル引用回数順公開年順タイトル順	引用先引用先	年
Spline models for observational data G Wahba Society for industrial and applied mathematics, 1990	10708	1990
Smoothing noisy data with spline functions: estimating the correct degree of smoothing by the method of generalized cross-validation P Craven, G Wahba Numerische mathematik 31 (4), 377-403, 1978	5347	1978
Generalized cross-validation as a method for choosing a good ridge parameter GH Golub, M Heath, G Wahba Technometrics 21 (2), 215-223, 1979	5337	1979
Some results on Tchebycheffian spline functions G Kimeldorf, G Wahba Journal of mathematical analysis and applications 33 (1), 82-95, 1971	2025	1971
A least squares estimate of satellite attitude G Wahba SIAM review 7 (3), 409-409, 1965	1687	1965
A correspondence between Bayesian estimation on stochastic processes and smoothing by splines GS Kimeldorf, G Wahba The Annals of Mathematical Statistics 41 (2), 495-502, 1970	1338	1970
Multicategory support vector machines: Theory and application to the classification of microarray data and satellite radiance data Y Lee, Y Lin, G Wahba Journal of the American Statistical Association 99 (465), 67-81, 2004	1120	2004
Practical approximate solutions to linear operator equations when the data are noisy G Wahba SIAM journal on numerical analysis 14 (4), 651-667, 1977	1112	1977
Bayesian “confidence intervals” for the cross‐validated smoothing spline G Wahba Journal of the Royal Statistical Society: Series B (Methodological) 45 (1 …, 1983	937	1983
Improper priors, spline smoothing and the problem of guarding against model errors in regression G Wahba Journal of the Royal Statistical Society Series B: Statistical Methodology …, 1978	863	1978
Some new mathematical methods for variational objective analysis using splines and cross validation G Wahba, J Wendelberger Monthly weather review 108 (8), 1122-1143, 1980	793	1980
A comparison of GCV and GML for choosing the smoothing parameter in the generalized spline smoothing problem G Wahba The annals of statistics, 1378-1402, 1985	721	1985
Support vector machines, reproducing kernel Hilbert spaces and the randomized GACV G Wahba Advances in Kernel Methods-Support Vector Learning 6, 69-87, 1999	710	1999
A completely automatic french curve: fitting spline functions by cross validation G Wahba, S Wold Communications in Statistics-Theory and Methods 4 (1), 1-17, 1975	660	1975
Support vector machines for classification in nonstandard situations Y Lin, Y Lee, G Wahba Machine learning 46, 191-202, 2002	566	2002
Spline interpolation and smoothing on the sphere G Wahba SIAM Journal on Scientific and Statistical Computing 2 (1), 5-16, 1981	550	1981
Smoothing noisy data with spline functions G Wahba Numerische mathematik 24 (5), 383-393, 1975	494	1975
A note on the lasso and related procedures in model selection C Leng, Y Lin, G Wahba Statistica Sinica, 1273-1284, 2006	434	2006
Smoothing spline ANOVA for exponential families, with application to the Wisconsin Epidemiological Study of Diabetic Retinopathy: the 1994 Neyman Memorial Lecture G Wahba, Y Wang, C Gu, R Klein, B Klein The Annals of Statistics 23 (6), 1865-1895, 1995	357	1995
Automatic smoothing of the log periodogram G Wahba Journal of the American Statistical Association 75 (369), 122-132, 1980	295	1980

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