On the versatility and polyvalence of certain statistical learning machines
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2019
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Mark
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Vysoké učení technické v Brně, Fakulta strojního inženýrství, Ústav matematiky
Abstract
As data science and its flurry of lucrative career opportunities continue to dominatestrategic planning meetings at companies and universities around the world, it isremarkable to notice that mathematics, the queen of all sciences, is still called uponto play a central role. I use mathematics here in senso lato to mean mathematicalsciences in general, including algebra, analysis, probability, statistics and theoret-ical computer science. Indeed all the statistical learning machines and traditionalstatistical methods permeating the articles of this special issue have in common thefact they all rest on strong mathematical foundations, even though some of the vastmathematical details are not shown here in some cases due to space constraints.
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Mathematics for Applications. 2019 vol. 8, č. 2, s. 97-99. ISSN 1805-3629
http://ma.fme.vutbr.cz/archiv/8_2/ma_8_2_0_editorial.pdf
http://ma.fme.vutbr.cz/archiv/8_2/ma_8_2_0_editorial.pdf
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en
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© Vysoké učení technické v Brně, Fakulta strojního inženýrství, Ústav matematiky