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UID:539@lincs.fr
DTSTART;TZID=Europe/Paris:20200527T110000
DTEND;TZID=Europe/Paris:20200527T120000
DTSTAMP:20200527T122537Z
URL:https://www.lincs.fr/events/support-vector-networks/
SUMMARY:Support-vector networks
DESCRIPTION:Cortes\, C.\, Vapnik\, V. Support-vector networks. Mach Learn
 20\, 273–297 (1995). https://doi.org/10.1007/BF00994018 .\n\nAbstract of
 the paper:\n\n"The support-vector network is a new leaming machine for
 two-group classification problems. The machine conceptually implements the
 following idea: input vectors are non-linearly mapped to a very high-
 dimension feature space. In this feature space a linear decision surface is
 constructed. Special properties of the decision surface ensures high
 generalization ability of the learning machine. The idea behind the
 support-vector network was previously implemented for the restricted case
 where the training data can be separated without errors. We here extend
 this result to non-separable training data. High generalization ability of
 support-vector networks utilizing polynomial input transformations is
 demonstrated. We also compare the performance of the support-vector network
 to various classical learning algorithms that all took part in a benchmark
 study of Optical Character Recognition."\n\nTalk material available here:
 https://github.com/yokaiAG/DataNets-Course\n\n
CATEGORIES:Network Theory,Working Group,Youtube
LOCATION:Paris-Rennes Room (EIT Digital)\, 23 avenue d'Italie\, 75013
 Paris\, France
X-APPLE-STRUCTURED-LOCATION;VALUE=URI;X-ADDRESS=23 avenue d'Italie\, 75013
 Paris\, France;X-APPLE-RADIUS=100;X-TITLE=Paris-Rennes Room (EIT
 Digital):geo:0,0
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