Graph Condensation for Large Factor Models
- Authors: Chetverushkin B.N.1, Sudakov V.A.1, Titov Y.P.2
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Affiliations:
- Keldysh Institute of Applied Mathematics (Russian Academy of Sciences)
- Moscow Aviation Institute (National Research University)
- Issue: Vol 517, No 1 (2024)
- Pages: 66-73
- Section: MATHEMATICS
- URL: https://rjeid.com/2686-9543/article/view/647988
- DOI: https://doi.org/10.31857/S2686954324030119
- EDN: https://elibrary.ru/YAYMIS
- ID: 647988
Cite item
Abstract
The paper proposes an original method for processing large factor models based on graph condensation using machine learning models and artificial neural networks. The proposed mathematical apparatus can be used in problems of planning and managing complex organizational and technical systems, in optimizing large socio-economic objects on the scale of state sectors, to solve problems of preserving the health of the nation (searching for compatibility when taking medications, optimizing resource provision for healthcare).
Keywords
About the authors
B. N. Chetverushkin
Keldysh Institute of Applied Mathematics (Russian Academy of Sciences)
Author for correspondence.
Email: office@keldysh.ru
Academician of the RAS
Russian Federation, MoscowV. A. Sudakov
Keldysh Institute of Applied Mathematics (Russian Academy of Sciences)
Email: sudakov@ws-dss.com
Russian Federation, Moscow
Yu. P. Titov
Moscow Aviation Institute (National Research University)
Email: kalengul@mail.ru
Russian Federation, Moscow
References
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