Embracing statistical challenges in the information technology age
Identifieur interne : 001011 ( Main/Exploration ); précédent : 001010; suivant : 001012Embracing statistical challenges in the information technology age
Auteurs : BIN YU [États-Unis]Source :
- Technometrics [ 0040-1706 ] ; 2007.
Descripteurs français
- Pascal (Inist)
- Wicri :
- topic : Enseignement, Intelligence artificielle.
English descriptors
- KwdEn :
Abstract
This article examines the role of statistics in the age of information technology (IT). It begins by examining the current state of IT and of the cyberinfrastructure initiative aimed at integrating the technologies into science, engineering, and education to convert massive amounts of data into useful information. Selected applications from science and text processing are introduced to provide concrete examples of massive data sets and the statistical challenges that they pose. The thriving field of machine learning is reviewed as an example of current achievements driven by computations and IT. Ongoing challenges that we face in the IT revolution are also highlighted. The paper concludes that for the healthy future of our field, computer technologies have to be integrated into statistics, and statistical thinking in turn must be integrated into computer technologies.
Affiliations:
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Le document en format XML
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<term>Teaching</term>
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<term>Very large databases</term>
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<front><div type="abstract" xml:lang="en">This article examines the role of statistics in the age of information technology (IT). It begins by examining the current state of IT and of the cyberinfrastructure initiative aimed at integrating the technologies into science, engineering, and education to convert massive amounts of data into useful information. Selected applications from science and text processing are introduced to provide concrete examples of massive data sets and the statistical challenges that they pose. The thriving field of machine learning is reviewed as an example of current achievements driven by computations and IT. Ongoing challenges that we face in the IT revolution are also highlighted. The paper concludes that for the healthy future of our field, computer technologies have to be integrated into statistics, and statistical thinking in turn must be integrated into computer technologies.</div>
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