Some Implications of Interval Approach to Dimension for Network Complexity

0510711 - ÚI 2020 ES eng A - Abstrakt
Kůrková, Věra
Some Implications of Interval Approach to Dimension for Network Complexity.
ESCIM 2019. Book of Abstracts. Cádiu: University of Cádiz, 2019 - (Kóczy, L.; Medina, J.). s. 59-60. ISBN 978-84-09-14600-0.
[ESCIM 2019: European Symposium on Computational Intelligence and Mathematics /11./. 02.10.2019-05.10.2019, Toledo]
Grant CEP: GA ČR(CZ) GA18-23827S
Institucionální podpora: RVO:67985807
Klíčová slova: quasiorthogonal dimension * sparsity of feedforward networks * high-dimensional geometry * concentration of measure * covering numbers
Obor OECD: Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)

An interval approach to the concept of dimension is presented. Implications of exponentially growing quasiorthogonal dimension for estimates of network complexity are analysed. Bounds on correlations of computational tasks represented by high-dimensional vectors are derived. Network complexity is analyzed from the point of view od the concentration of measure phenomen.
Trvalý link: http://hdl.handle.net/11104/0301114