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A User-Specific Machine Learning Approach for Improving Touch Accuracy on Mobile Devices Daryl Weir, Simon Rogers, Roderick Murray-Smith School of Computing Science University of Glasgow
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Document Date: 2013-02-07 08:13:42


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File Size: 2,44 MB

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City

Saarbrucken / Cambridge / /

Company

Nokia / Google / Glasgow 18 Lilybank / /

Country

Germany / United States / /

Currency

USD / /

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Facility

Mobile Devices Daryl Weir / Computing Science University of Glasgow / /

IndustryTerm

sparse regression algorithm / post-processing step / non-parametric regression algorithm / real time / natural languages technologies / mobile devices / native algorithm / particular device / touch-screen device / touchscreen devices / /

OperatingSystem

Android / /

Organization

uk Markus L¨ochtefeld German Research Center / Computing Science University of Glasgow / US Federal Reserve / Roderick Murray-Smith School / /

Person

Simon Rogers / Button Figure / /

Position

Author / linear model / model complex RELATED WORK Even though HCI research / simple data collector / /

Product

N9 / /

ProgrammingLanguage

Python / /

ProvinceOrState

Massachusetts / /

PublishedMedium

Machine Learning / /

Technology

non-parametric regression algorithm / N9s native algorithm / artificial intelligence / N9s algorithm / smartphones / smartphone / GPS / sparse regression algorithm / mobile phones / Machine Learning / Android / mobile device / natural languages technologies / native algorithm / Mobile Devices / /

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