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@article{DANMA_2020_490_a16, author = {S. V. Kurochkin}, title = {Absence of bottlenecks in a neural network determines its generic functional properties}, journal = {Doklady Rossijskoj akademii nauk. Matematika, informatika, processy upravleni\^a}, pages = {74--77}, publisher = {mathdoc}, volume = {490}, year = {2020}, language = {ru}, url = {http://geodesic.mathdoc.fr/item/DANMA_2020_490_a16/} }
TY - JOUR AU - S. V. Kurochkin TI - Absence of bottlenecks in a neural network determines its generic functional properties JO - Doklady Rossijskoj akademii nauk. Matematika, informatika, processy upravleniâ PY - 2020 SP - 74 EP - 77 VL - 490 PB - mathdoc UR - http://geodesic.mathdoc.fr/item/DANMA_2020_490_a16/ LA - ru ID - DANMA_2020_490_a16 ER -
%0 Journal Article %A S. V. Kurochkin %T Absence of bottlenecks in a neural network determines its generic functional properties %J Doklady Rossijskoj akademii nauk. Matematika, informatika, processy upravleniâ %D 2020 %P 74-77 %V 490 %I mathdoc %U http://geodesic.mathdoc.fr/item/DANMA_2020_490_a16/ %G ru %F DANMA_2020_490_a16
S. V. Kurochkin. Absence of bottlenecks in a neural network determines its generic functional properties. Doklady Rossijskoj akademii nauk. Matematika, informatika, processy upravleniâ, Tome 490 (2020), pp. 74-77. http://geodesic.mathdoc.fr/item/DANMA_2020_490_a16/
[1] Cybenko G.V., “Approximation by Superpositions of a Sigmoidal function”, Mathematics of Control Signals and Systems, 2:4 (1989), 303–314 | DOI | MR | Zbl
[2] Pinkus A., “Approximation Theory of the MLP Model in Neural Networks”, Acta Numerica, 8 (1999), 143–195 | DOI | MR | Zbl
[3] Zhuravlev Yu.I., Rudakov K.V., “Ob algebraicheskoi korrektsii protsedur obrabotki (preobrazovaniya) informatsii”, Problemy prikladnoi matematiki i informatiki, Nauka, M., 1987, 187–198 | MR
[4] Kurochkin S.V., “Raspoznavanie gomotopicheskogo tipa ob'ekta s pomoschyu differentsialno-topologicheskikh invariantov approksimiruyuschego otobrazheniya”, Kompyuternaya optika, 43:4 (2019), 611–617 | DOI
[5] Postnikov M.M., Vvedenie v teoriyu Morsa, Nauka, M., 1971 | MR
[6] Arnold V., “Smooth functions statistics”, Funct. Anal. Other Math, 2006, no. 1, 111–118 | DOI | MR | Zbl
[7] Gudfellou Ya., Bendzhio I., Kurvill A., Glubokoe obuchenie, DMK Press, M., 2017
[8] Le C., “A note on Optimization with Morse Polynomials”, Commun. Korean Math. Soc, 33:2 (2018), 671–676 | DOI | MR | Zbl
[9] Banyaga A., Hurtubise D., Lectures on Morse Homology, Kluwer Texts Math. Sci., 29, Kluwer Acad. Publ., Dordrecht, 2004 | DOI | MR | Zbl
[10] Prasolov V.V., Elementy kombinatornoi i differentsialnoi topologii, MTsNMO, M., 2014
[11] Baksalary J.K., Kala R., “The Matrix Equation AX-YB = C”, Linear Algebra and Its Applications, 30 (1979), 41–43 | DOI | MR
[12] Prasolov V.V., Zadachi i teoremy lineinoi algebry, MTsNMO, M., 2015
[13] Nicolaescu L., An Invitation to Morse Theory, Springer, 2011 | MR | Zbl
[14] Carlsson G., “Topology and Data”, Bulletin of the American Mathematical Society, 46:2 (2009), 255–308 | DOI | MR | Zbl