Models and Algorithms for Graph centrality grounded on Nonlinear Eigenvalues Techniques

Project Information

MAGNET

Grant agreement ID: 744014

DOI

10.3030/744014

Project closed

EC signature date 20 March 2017

Start date 1 July 2017

End date 30 June 2019

Funded under

• EXCELLENT SCIENCE - Marie Skłodowska-Curie Actions

Total cost

€ 183 454,80

EU contribution

€ 183 454,80

Coordinated by

UNIVERSITY OF STRATHCLYDE
United Kingdom

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Links to deliverables and publications from FP7 projects, as well as links to some specific result types such as dataset and software, are dynamically retrieved from OpenAIRE .

Publications

Book chapters (3)

Multi-Dimensional, Multilayer, Nonlinear and Dynamic HITS

Author(s): Francesca Arrigo, Francesco Tudisco
Published in: Proceedings of the 2019 SIAM International Conference on Data Mining, 2019, Page(s) 369-377, ISBN 978-1-61197-567-3
Publisher: Society for Industrial and Applied Mathematics
DOI: 10.1137/1.9781611975673.42

The Power Mean Laplacian for Multilayer Graph Clustering

Author(s): Mercado, Pedro; Gautier, Antoine; Tudisco, Francesco; Hein, Matthias
Published in: Proceedings of the Twenty-First International Conference on Artificial Intelligence and Statistics; Proceedings of Machine Learning Research, 2018, Page(s) PMLR 84:1828-1838
Publisher: PMLR

Spectral Clustering of Signed Graphs via Matrix Power Means

Author(s): Pedro Mercado, Francesco Tudisco, Matthias Hein
Published in: Proceedings of the 36th International Conference on Machine Learning; Proceedings of Machine Learning Research, 2019
Publisher: PMLR

Other (4)

The Perron-Frobenius theorem for multi-homogeneous mappings

Author(s): Gautier, Antoine; Tudisco, Francesco; Hein, Matthias
Published in: SIAM Journal on Matrix Analysis and Applications, 2019
Publisher: Society for Industrial and Applied Mathematics

A unifying Perron-Frobenius theorem for nonnegative tensors via multi-homogeneous maps

Author(s): Gautier, Antoine; Tudisco, Francesco; Hein, Matthias
Published in: SIAM Journal on Matrix Analysis and Applications, 2019
Publisher: Society for Industrial and Applied Mathematics

The contractivity of cone-preserving multilinear mappings

Author(s): Gautier, Antoine; Tudisco, Francesco
Published in: Nonlinearity, 2019
Publisher: IOP Publishing Ltd & London Mathematical Society

A fast and robust kernel optimization method for core--periphery detection in directed and weighted graphs

Author(s): Francesco Tudisco, Desmond J. Higham
Published in: Applied Network Science, 2019
Publisher: Springer Open

Peer reviewed articles (5)

Community Detection in Networks via Nonlinear Modularity Eigenvectors

Author(s): Francesco Tudisco, Pedro Mercado, Matthias Hein
Published in: SIAM Journal on Applied Mathematics, Issue 78/5, 2018, Page(s) 2393-2419, ISSN 0036-1399
Publisher: Society for Industrial and Applied Mathematics
DOI: 10.1137/17m1144143

The expected adjacency and modularity matrices in the degree corrected stochastic block model

Author(s): Dario Fasino, Francesco Tudisco
Published in: Special Matrices, Issue 6/1, 2018, Page(s) 110-121, ISSN 2300-7451
Publisher: De Gruyter
DOI: 10.1515/spma-2018-0010

On the Stability of Network Indices Defined by Means of Matrix Functions

Author(s): Stefano Pozza, Francesco Tudisco
Published in: SIAM Journal on Matrix Analysis and Applications, Issue 39/4, 2018, Page(s) 1521-1546, ISSN 0895-4798
Publisher: Society for Industrial and Applied Mathematics
DOI: 10.1137/17m1133920

Node and Layer Eigenvector Centralities for Multiplex Networks

Author(s): Francesco Tudisco, Francesca Arrigo, Antoine Gautier
Published in: SIAM Journal on Applied Mathematics, Issue 78/2, 2018, Page(s) 853-876, ISSN 0036-1399
Publisher: Society for Industrial and Applied Mathematics
DOI: 10.1137/17m1137668

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

Author(s): Francesco Tudisco, Desmond J. Higham
Published in: SIAM Journal on Mathematics of Data Science, Issue 1/2, 2019, Page(s) 269-292, ISSN 2577-0187
Publisher: Society for Industrial and Applied Mathematics
DOI: 10.1137/18m1183558