output
20192024
most citedGrowing scale-free simplices

73 citations

10 papers

cs.LG2024★ 1 cited

Local Methods with Adaptivity via Scaling

Savelii Chezhegov, Sergey Skorik, Nikolas Khachaturov +5

The rapid development of machine learning and deep learning has introduced increasingly complex optimization challenges that must be addressed. Indeed, training modern, advanced mo…

physics.soc-ph2022★ 29 cited

Why are there six degrees of separation in a social network?

Ivan Samoylenko, David Aleja, Eva Primo +11

A wealth of evidence shows that real world networks are endowed with the small-world property i.e., that the maximal distance between any two of their nodes scales logarithmically…

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.OC2020★ 26 cited

Recent theoretical advances in decentralized distributed convex optimization

Eduard Gorbunov, Alexander Rogozin, Aleksandr Beznosikov +2

In the last few years, the theory of decentralized distributed convex optimization has made significant progress. The lower bounds on communications rounds and oracle calls have ap…

nlin.AO2020★ 53 cited

D-dimensional oscillators in simplicial structures: odd and even dimensions display different synchronization scenarios

X. Dai, K. Kovalenko, M. Molodyk +8

From biology to social science, the functioning of a wide range of systems is the result of elementary interactions which involve more than two constituents, so that their descript…