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Nonlinear estimation and classification
Researchers in many disciplines face the formidable task of analyzing massive amounts of high-dimensional and highly-structured data This is due in part to recent advances in data collection and computing technologies As a result, fundamental statistical research is being undertaken in a variety of...
Autores principales: | , , , , |
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Lenguaje: | eng |
Publicado: |
Springer
2003
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Materias: | |
Acceso en línea: | https://dx.doi.org/10.1007/978-0-387-21579-2 http://cds.cern.ch/record/1663979 |
_version_ | 1780935246895644672 |
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author | Denison, David Hansen, Mark Holmes, Christopher Mallick, Bani Yu, Bin |
author_facet | Denison, David Hansen, Mark Holmes, Christopher Mallick, Bani Yu, Bin |
author_sort | Denison, David |
collection | CERN |
description | Researchers in many disciplines face the formidable task of analyzing massive amounts of high-dimensional and highly-structured data This is due in part to recent advances in data collection and computing technologies As a result, fundamental statistical research is being undertaken in a variety of different fields Driven by the complexity of these new problems, and fueled by the explosion of available computer power, highly adaptive, non-linear procedures are now essential components of modern "data analysis," a term that we liberally interpret to include speech and pattern recognition, classification, data compression and signal processing The development of new, flexible methods combines advances from many sources, including approximation theory, numerical analysis, machine learning, signal processing and statistics The proposed workshop intends to bring together eminent experts from these fields in order to exchange ideas and forge directions for the future |
id | cern-1663979 |
institution | Organización Europea para la Investigación Nuclear |
language | eng |
publishDate | 2003 |
publisher | Springer |
record_format | invenio |
spelling | cern-16639792021-04-21T21:18:57Zdoi:10.1007/978-0-387-21579-2http://cds.cern.ch/record/1663979engDenison, DavidHansen, MarkHolmes, ChristopherMallick, BaniYu, BinNonlinear estimation and classificationMathematical Physics and MathematicsResearchers in many disciplines face the formidable task of analyzing massive amounts of high-dimensional and highly-structured data This is due in part to recent advances in data collection and computing technologies As a result, fundamental statistical research is being undertaken in a variety of different fields Driven by the complexity of these new problems, and fueled by the explosion of available computer power, highly adaptive, non-linear procedures are now essential components of modern "data analysis," a term that we liberally interpret to include speech and pattern recognition, classification, data compression and signal processing The development of new, flexible methods combines advances from many sources, including approximation theory, numerical analysis, machine learning, signal processing and statistics The proposed workshop intends to bring together eminent experts from these fields in order to exchange ideas and forge directions for the futureSpringeroai:cds.cern.ch:16639792003 |
spellingShingle | Mathematical Physics and Mathematics Denison, David Hansen, Mark Holmes, Christopher Mallick, Bani Yu, Bin Nonlinear estimation and classification |
title | Nonlinear estimation and classification |
title_full | Nonlinear estimation and classification |
title_fullStr | Nonlinear estimation and classification |
title_full_unstemmed | Nonlinear estimation and classification |
title_short | Nonlinear estimation and classification |
title_sort | nonlinear estimation and classification |
topic | Mathematical Physics and Mathematics |
url | https://dx.doi.org/10.1007/978-0-387-21579-2 http://cds.cern.ch/record/1663979 |
work_keys_str_mv | AT denisondavid nonlinearestimationandclassification AT hansenmark nonlinearestimationandclassification AT holmeschristopher nonlinearestimationandclassification AT mallickbani nonlinearestimationandclassification AT yubin nonlinearestimationandclassification |