Graph Condensation for Large Factor Models

Academician of the RAS B. N. Chetverushkin^a^,*, V. A. Sudakov^a^,**, and Yu. P. Titov^b^,***

^aFederal Research Center Keldysh Institute of Applied Mathematics, Russian Academy of Sciences, Moscow, Russia

^bMoscow Aviation Institute (National Research University), Moscow, Russia

email: *office@keldysh.ru
email: **sudakov@ws-dss.com
email: ***kalengul@mail.ru

Received 17 January, 2024

Abstract— An original method for processing large factor models based on graph condensation using machine learning models and artificial neural networks is developed. The proposed mathematical apparatus can be used to plan and manage complex organizational and technical systems, to optimize large socioeconomic objects of national scale, and to solve problems of preserving the health of the nation (searching for compatibility of medications and optimizing health care resources).

Keywords: factor model, graph condensation, clustering, eigenvector, eigenvalues

DOI: 10.1134/S1064562424702090