Geodesic
Machine learning of the~well-known things
Teoretičeskaâ i matematičeskaâ fizika, Tome 214 (2023) no. 3, pp. 517-528

Voir la notice de l'article provenant de la source Math-Net.Ru

Machine learning (ML) in its current form implies that the answer to any problem can be well approximated by a function of a very peculiar form: a specially adjusted iteration of Heaviside theta-functions. It is natural to ask whether the answers to questions that we already know can be naturally represented in this form. We provide elementary and yet nonevident examples showing that this is indeed possible, and suggest to look for a systematic reformulation of existing knowledge in an ML-consistent way. The success or failure of these attempts can shed light on a variety of problems, both scientific and epistemological.
Keywords: exact approaches to QFT, nonlinear algebra, machine learning, steepest descent method. 
@article{TMF_2023_214_3_a8,
     author = {V. V. Dolotin and A. Yu. Morozov and A. V. Popolitov},
     title = {Machine learning of the~well-known things},
     journal = {Teoreti\v{c}eska\^a i matemati\v{c}eska\^a fizika},
     pages = {517--528},
     publisher = {mathdoc},
     volume = {214},
     number = {3},
     year = {2023},
     language = {ru},
     url = {http://geodesic.mathdoc.fr/item/TMF_2023_214_3_a8/}
}
TY  - JOUR
AU  - V. V. Dolotin
AU  - A. Yu. Morozov
AU  - A. V. Popolitov
TI  - Machine learning of the~well-known things
JO  - Teoretičeskaâ i matematičeskaâ fizika
PY  - 2023
SP  - 517
EP  - 528
VL  - 214
IS  - 3
PB  - mathdoc
UR  - http://geodesic.mathdoc.fr/item/TMF_2023_214_3_a8/
LA  - ru
ID  - TMF_2023_214_3_a8
ER  - 
%0 Journal Article
%A V. V. Dolotin
%A A. Yu. Morozov
%A A. V. Popolitov
%T Machine learning of the~well-known things
%J Teoretičeskaâ i matematičeskaâ fizika
%D 2023
%P 517-528
%V 214
%N 3
%I mathdoc
%U http://geodesic.mathdoc.fr/item/TMF_2023_214_3_a8/
%G ru
%F TMF_2023_214_3_a8
V. V. Dolotin; A. Yu. Morozov; A. V. Popolitov. Machine learning of the~well-known things. Teoretičeskaâ i matematičeskaâ fizika, Tome 214 (2023) no. 3, pp. 517-528. http://geodesic.mathdoc.fr/item/TMF_2023_214_3_a8/