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20162022
most citedSpectral Clustering of Signed Graphs via Matrix Power Means

13 citations · 27 across the 4 of their papers we have counts for

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9 papers · 1 filter

cs.SI2021

Node and Edge Nonlinear Eigenvector Centrality for Hypergraphs

Francesco Tudisco, Desmond J. Higham

Network scientists have shown that there is great value in studying pairwise interactions between components in a system. From a linear algebra point of view, this involves definin…

cs.SI2020

Nonlocal PageRank

Stefano Cipolla, Fabio Durastante, Francesco Tudisco

In this work we introduce and study a nonlocal version of the PageRank. In our approach, the random walker explores the graph using longer excursions than just moving between neigh…

cs.SI2019

A framework for second order eigenvector centralities and clustering coefficients

Francesca Arrigo, Desmond J. Higham, Francesco Tudisco

We propose and analyse a general tensor-based framework for incorporating second order features into network measures. This approach allows us to combine traditional pairwise links…

cs.SI2019

Total variation based community detection using a nonlinear optimization approach

Andrea Cristofari, Francesco Rinaldi, Francesco Tudisco

Maximizing the modularity of a network is a successful tool to identify an important community of nodes. However, this combinatorial optimization problem is known to be NP-complete…

cs.SI2018

Multi-Dimensional, Multilayer, Nonlinear and Dynamic HITS

Francesca Arrigo, Francesco Tudisco

We introduce a ranking model for temporal multi-dimensional weighted and directed networks based on the Perron eigenvector of a multi-homogeneous order-preserving map. The model ex…

cs.SI2018

A Nonlinear Spectral Method for Core--Periphery Detection in Networks

Francesco Tudisco, Desmond J. Higham

We derive and analyse a new iterative algorithm for detecting network core--periphery structure. Using techniques in nonlinear Perron-Frobenius theory, we prove global convergence…