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Description
  • Learning algorithm based on Kolmogorov theorem concerning composition of n-dimensional continuous function from one-dimensional continuous functions. The approach by Sprecher who proposed a numerical impl. is followed. The improved version of the alg. is presented where key impl. problems have been solved.
  • Learning algorithm based on Kolmogorov theorem concerning composition of n-dimensional continuous function from one-dimensional continuous functions. The approach by Sprecher who proposed a numerical impl. is followed. The improved version of the alg. is presented where key impl. problems have been solved. (en)
Title
  • Towards Feasible Learning Algorithm Based on Kolmogorov Theorem.
  • Towards Feasible Learning Algorithm Based on Kolmogorov Theorem. (en)
skos:prefLabel
  • Towards Feasible Learning Algorithm Based on Kolmogorov Theorem.
  • Towards Feasible Learning Algorithm Based on Kolmogorov Theorem. (en)
skos:notation
  • RIV/67985807:_____/00:06000158!RIV/2003/AV0/A06003/N
http://linked.open.../vavai/riv/strany
  • 915;920
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  • P(GA201/99/0092), P(GA201/99/P057), P(IAB1030006), Z(AV0Z1030915)
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  • 729442
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  • RIV/67985807:_____/00:06000158
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  • N/A (en)
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  • [B211D494EF71]
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  • Las Vegas [US]
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  • Las Vegas
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  • Proceedings of the International Conference on Artificial Intelligence.
http://linked.open...in/vavai/riv/obor
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  • Neruda, Roman
  • Drkošová, Jitka
  • Štědrý, Arnošt
http://linked.open...vavai/riv/typAkce
http://linked.open.../riv/zahajeniAkce
http://linked.open...n/vavai/riv/zamer
number of pages
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  • CSREA Press
https://schema.org/isbn
  • 1-892512-57-2
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