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20172025
most citedContrarians synchronize beyond the limit of pairwise interactions

74 citations

Showing 2021Show all

6 papers · 1 filter

physics.soc-ph2021★ 60 cited

Vector Centrality in Hypergraphs

Kirill Kovalenko, Miguel Romance, Ekaterina Vasilyeva +9

Identifying the most influential nodes in networked systems is of vital importance to optimize their function and control. Several scalar metrics have been proposed to that effect,…

physics.soc-ph2021★ 6 cited

Predicting transitions in cooperation levels from network connectivity

A. Zhuk, I. Sendiña-Nadal, I. Leyva +4

Networks determine our social circles and the way we cooperate with others. We know that topological features like hubs and degree assortativity affect cooperation, and we know tha…

math.OC2021★ 3 cited

Near-Optimal Decentralized Algorithms for Saddle Point Problems over Time-Varying Networks

Aleksandr Beznosikov, Alexander Rogozin, Dmitry Kovalev +1

Decentralized optimization methods have been in the focus of optimization community due to their scalability, increasing popularity of parallel algorithms and many applications. In…

physics.soc-ph2021★ 74 cited

Contrarians synchronize beyond the limit of pairwise interactions

K. Kovalenko, X. Dai, K. Alfaro-Bittner +3

We give evidence that a population of pure contrarians globally coupled D-dimensional Kuramoto oscillators reaches a collective synchronous state when the interplay between the uni…

math.CO2021★ 6 cited

Constructing 5-chromatic unit distance graphs embedded in the Euclidean plane and two-dimensional spheres

Vsevolod Voronov, Anna Neopryatnaya, Eugene Dergachev

This paper is devoted to the development of algorithms for finding unit distance graphs with chromatic number greater than 4, embedded in a two-dimensional sphere or plane. Such gr…

math.OC2021★ 4 cited

One-Point Gradient-Free Methods for Smooth and Non-Smooth Saddle-Point Problems

Aleksandr Beznosikov, Vasilii Novitskii, Alexander Gasnikov

In this paper, we analyze gradient-free methods with one-point feedback for stochastic saddle point problems . For non-smooth and smooth cases, we present…