Probabilistic Bounds for Approximation by Neural Networks
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F67985807%3A_____%2F19%3A00507969" target="_blank" >RIV/67985807:_____/19:00507969 - isvavai.cz</a>
Result on the web
<a href="http://dx.doi.org/10.1007/978-3-030-30487-4_33" target="_blank" >http://dx.doi.org/10.1007/978-3-030-30487-4_33</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1007/978-3-030-30487-4_33" target="_blank" >10.1007/978-3-030-30487-4_33</a>
Alternative languages
Result language
angličtina
Original language name
Probabilistic Bounds for Approximation by Neural Networks
Original language description
A probabilistic model describing relevance of tasks to be computed by a class of feedforward networks is studied. Bounds on correlations of network input-output functions with almost all randomly-chosen functions are derived. Impact of sizes of function domains on correlations are analyzed from the point of view of the concentration of measure phenomenon. It is shown that on large domains, errors of approximation of randomly chosen functions by fixed input-output functions are almost deterministic.
Czech name
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Czech description
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Classification
Type
D - Article in proceedings
CEP classification
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OECD FORD branch
10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)
Result continuities
Project
<a href="/en/project/GA19-05704S" target="_blank" >GA19-05704S: FoNeCo: Analytical Foundations of Neurocomputing</a><br>
Continuities
I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace
Others
Publication year
2019
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Article name in the collection
Artificial Neural Networks and Machine Learning – ICANN 2019: Theoretical Neural Computation. Proceedings, Part I
ISBN
978-3-030-30486-7
ISSN
0302-9743
e-ISSN
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Number of pages
11
Pages from-to
418-428
Publisher name
Springer
Place of publication
Cham
Event location
Munich
Event date
Sep 17, 2019
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
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