| 词条 | Grace Wahba |
| 释义 |
| name = Grace Wahba | image = | image_size = | caption = | birth_date = {{birth date and age|1934|08|03|mf=y}} | birth_place = | death_date = | death_place = | nationality = American | fields = Mathematics, Statistics, Machine Learning | workplaces = University of Wisconsin–Madison | alma_mater = Stanford University University of Maryland, College Park Cornell University | doctoral_advisor = Emanuel Parzen | doctoral_students = {{plainlist|1=
Grace Wahba (born August 3, 1934) is a now-retired I. J. Schoenberg-Hilldale Professor of Statistics at the University of Wisconsin–Madison.[1] She is a pioneer in methods for smoothing noisy data. Best known for the development of generalized cross-validation[2] and "Wahba's problem",[1] 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),[1] 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[3]. 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. Awards and honorsWahba is a member of the National Academy of Sciences,[4] and a fellow of several academic societies including the American Academy of Arts and Sciences, the American Association for the Advancement of Science, the American Statistical Association, and the Institute of Mathematical Statistics.[5] Over the years she has received a selection of notable awards in the statistics community:
References1. ^1 2 {{Cite web|url=https://news.wisc.edu/breaking-ground-with-grace/|title=Breaking ground with Grace|website=news.wisc.edu|language=en-US|access-date=2018-11-16}} 2. ^{{Cite journal|last=Craven|first=Peter|last2=Wahba|first2=Grace|date=1978-12-01|title=Smoothing noisy data with spline functions|url=https://doi.org/10.1007/BF01404567|journal=Numerische Mathematik|language=en|volume=31|issue=4|pages=377–403|doi=10.1007/BF01404567|issn=0945-3245}} 3. ^{{Cite book|url=https://epubs.siam.org/doi/book/10.1137/1.9781611970128|title=Spline Models for Observational Data|last=Wahba|first=G.|date=1990-01-01|publisher=Society for Industrial and Applied Mathematics|isbn=9780898712445|series=CBMS-NSF Regional Conference Series in Applied Mathematics|doi=10.1137/1.9781611970128}} 4. ^{{cite web|title=National Academy of Sciences|url=http://www.nasonline.org/member-directory/members/59761.html|website=National Academy of Sciences|accessdate=22 February 2016}} 5. ^{{cite web|url=http://www.stat.wisc.edu/~wahba/hons.txt|website=Grace Wahba: Honors|accessdate=22 February 2016|title=Graca Wahba: Honors}} 6. ^1 {{cite web|title=Institute of Mathematical Statistics|url=http://www.imstat.org/awards/copss_recipients.htm|website=Institute of Mathematical Statistics|accessdate=22 February 2016}} External links
22 : 1934 births|Living people|American statisticians|Fellows of the American Statistical Association|Members of the United States National Academy of Sciences|ISI highly cited researchers|20th-century mathematicians|21st-century mathematicians|Fellows of the Society for Industrial and Applied Mathematics|University of Wisconsin–Madison faculty|Cornell University alumni|University of Maryland, College Park alumni|Stanford University alumni|Bayesian statisticians|Women mathematicians|Women statisticians|Fellows of the American Academy of Arts and Sciences|Fellows of the American Association for the Advancement of Science|Fellows of the Institute of Mathematical Statistics|Machine learning researchers|20th-century women mathematicians|21st-century women mathematicians |
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