The Impact of Indirect Connections: The Case of Food Security Problem

Natalia Meshcheryakova

doi:10.1007/978-3-030-05414-4_7

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June 5, 2026

Neural Network Maps as a Method for Constructing Mathematical Models

Scientists from HSE University–Nizhny Novgorod and the Institute of Physics Belgrade, Serbia, are jointly exploring the application of machine learning techniques and neural networks to the study of nonlinear dynamics. Natalya Stankevich, Leading Research Fellow at the Laboratory of Topological Methods in Dynamics of the Faculty of Informatics, Mathematics, and Computer Science at HSE University–Nizhny Novgorod, spoke to the HSE News Service about this international project.

June 5, 2026

‘In the Age of Technology, It Is Interesting to Look into the Past and Think about What We Can Take from It

Polina Tabakova decided to apply for a Philology degree at HSE in Nizhny Novgorod because she grew up in Mari El and did not want to move far away from the Russian forests. In an interview for the Young Scientists of HSE University project, she spoke about the genre of the campus novel, the existential drama of Kolobok, and a blackout version of Eugene Onegin.

June 5, 2026

HSE Scientists Develop Method to Compress Large Language Models Without Losing Quality

Researchers from the AI and Digital Science Institute at the HSE Faculty of Computer Science have developed a new compression method for large language models such as GPT and LLaMA that reduces their size by 25–36% without additional training or significant loss of accuracy. This is the first approach to use mathematical transformations—specifically, rotations of model weights—to make models more amenable to compression with structured matrices. The study results have been published in ACL Findings 2025. The code is available on GitHub.

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The Impact of Indirect Connections: The Case of Food Security Problem

Ch. 7. P. 80–90.

Natalia Meshcheryakova

We propose a family of new measures for edge importance estimation. We focus on weighted directed networks where weights indicate the intensity of connections between nodes. We reward edges that increase node-tonode influence compared to direct connections between them. This approach allows to reveal hidden channels of the influence in networks. We apply the proposed model to food export/import networks in order to elucidate the most important trading relations. We compare the results with edge-betweenness centrality and investigate the interdependence between edge importance and centrality measures of corresponding source and sink nodes. The results are provided in dynamic.

Keywords: edge importance food security network indirect influence

Publication based on the results of:

A study of models of decision-making and analysis of complex structured data (2019)

In book

Studies in Computational Intelligence

* 2. Vol. 813: Complex Networks and Their Applications VII. , Springer, 2019.

New Centrality Measures in Networks: How to Take into Account the Parameters of the Nodes and Group Influence of Nodes to Nodes

Aleskerov F. T., Shvydun S., Meshcheryakova N., CRC Press, 2022.

Over the last number of years there has been a growing interest in the analysis of complex networks which describe a wide range of real-world systems in nature and society. Identification of the central elements in such networks is one of the key research areas. Solutions to this problem are important for making strategic decisions ...

Added: November 12, 2021