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Computational Intelligence and Mathematics for Tackling Complex Problems 2
- 1.0549873 - ÚI 2023 RIV CH eng M - Monography Chapter
Kůrková, Věra
Some Implications of Interval Approach to Dimension for Network Complexity.
Computational Intelligence and Mathematics for Tackling Complex Problems 2. Cham: Springer, 2022 - (Cornejo, M.; Kóczy, L.; Medina-Moreno, J.; Moreno-García, J.), s. 113-119. Studies in Computational Intelligence, 955. ISBN 978-3-030-88816-9
R&D Projects: GA ČR(CZ) GA18-23827S
Institutional support: RVO:67985807
Keywords : Quasiorthogonal dimension * Sparsity of feedforward networks * High-dimensional geometry * Concentration of measure * Covering numbers
OECD category: 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 analyzed. Bounds on correlations of computational tasks represented by high-dimensional vectors are derived. Network complexity is explored from the point of view of the concentration of measure phenomenon.
Permanent Link: http://hdl.handle.net/11104/0325766
Number of the records: 1