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- Grace_Wahba abstract "Grace Wahba (born August 3, 1934) is the I. J. Schoenberg Professor of Statistics at the University of Wisconsin–Madison. She is a pioneer in methods for smoothing noisy data. Best known for the development of generalized cross-validation and "Wahba's problem", she has developed methods with applications in demographic studies, machine learning, DNA microarrays, risk modeling, medical imaging, and climate prediction. She was educated at Cornell (B.A. 1956), University of Maryland, College Park (M.A. 1962) and Stanford (Ph.D. 1966), and worked in industry for several years before receiving her doctorate in 1966 and settling in Madison in 1967. She is the author of Spline Models for Observational Data. She was elected to the United States National Academy of Sciences in 2000 and received an honorary degree of Doctor of Science from the University of Chicago in 2007.".
- Grace_Wahba almaMater Stanford_University.
- Grace_Wahba birthDate "1934-08-03".
- Grace_Wahba birthYear "1934".
- Grace_Wahba doctoralAdvisor Emanuel_Parzen.
- Grace_Wahba field Mathematics.
- Grace_Wahba nationality United_States.
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- Grace_Wahba almaMater Stanford_University.
- Grace_Wahba birthDate "1934-08-03".
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- Grace_Wahba name "Grace Wahba".
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- Grace_Wahba shortDescription "American statistician".
- Grace_Wahba workplaces University_of_Wisconsin–Madison.
- Grace_Wahba description "American statistician".
- Grace_Wahba description "American statistician".
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- Grace_Wahba comment "Grace Wahba (born August 3, 1934) is the I. J. Schoenberg Professor of Statistics at the University of Wisconsin–Madison. She is a pioneer in methods for smoothing noisy data. Best known for the development of generalized cross-validation and "Wahba's problem", she has developed methods with applications in demographic studies, machine learning, DNA microarrays, risk modeling, medical imaging, and climate prediction. She was educated at Cornell (B.A.".
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