Models and Algorithms for Graph centrality grounded on Nonlinear Eigenvalues Techniques

Multi-Dimensional, Multilayer, Nonlinear and Dynamic HITS

Autori: Francesca Arrigo, Francesco Tudisco
Pubblicato in: Proceedings of the 2019 SIAM International Conference on Data Mining, 2019, Pagina/e 369-377, ISBN 978-1-61197-567-3
Editore: Society for Industrial and Applied Mathematics
DOI: 10.1137/1.9781611975673.42

The Power Mean Laplacian for Multilayer Graph Clustering

Autori: Mercado, Pedro; Gautier, Antoine; Tudisco, Francesco; Hein, Matthias
Pubblicato in: Proceedings of the Twenty-First International Conference on Artificial Intelligence and Statistics; Proceedings of Machine Learning Research, 2018, Pagina/e PMLR 84:1828-1838
Editore: PMLR

Spectral Clustering of Signed Graphs via Matrix Power Means

Autori: Pedro Mercado, Francesco Tudisco, Matthias Hein
Pubblicato in: Proceedings of the 36th International Conference on Machine Learning; Proceedings of Machine Learning Research, 2019
Editore: PMLR

The Perron-Frobenius theorem for multi-homogeneous mappings

Autori: Gautier, Antoine; Tudisco, Francesco; Hein, Matthias
Pubblicato in: SIAM Journal on Matrix Analysis and Applications, 2019
Editore: Society for Industrial and Applied Mathematics

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

Autori: Gautier, Antoine; Tudisco, Francesco; Hein, Matthias
Pubblicato in: SIAM Journal on Matrix Analysis and Applications, 2019
Editore: Society for Industrial and Applied Mathematics

The contractivity of cone-preserving multilinear mappings

Autori: Gautier, Antoine; Tudisco, Francesco
Pubblicato in: Nonlinearity, 2019
Editore: IOP Publishing Ltd & London Mathematical Society

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

Autori: Francesco Tudisco, Desmond J. Higham
Pubblicato in: Applied Network Science, 2019
Editore: Springer Open

Community Detection in Networks via Nonlinear Modularity Eigenvectors

Autori: Francesco Tudisco, Pedro Mercado, Matthias Hein
Pubblicato in: SIAM Journal on Applied Mathematics, Numero 78/5, 2018, Pagina/e 2393-2419, ISSN 0036-1399
Editore: Society for Industrial and Applied Mathematics
DOI: 10.1137/17m1144143

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

Autori: Dario Fasino, Francesco Tudisco
Pubblicato in: Special Matrices, Numero 6/1, 2018, Pagina/e 110-121, ISSN 2300-7451
Editore: De Gruyter
DOI: 10.1515/spma-2018-0010

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

Autori: Stefano Pozza, Francesco Tudisco
Pubblicato in: SIAM Journal on Matrix Analysis and Applications, Numero 39/4, 2018, Pagina/e 1521-1546, ISSN 0895-4798
Editore: Society for Industrial and Applied Mathematics
DOI: 10.1137/17m1133920

Node and Layer Eigenvector Centralities for Multiplex Networks

Autori: Francesco Tudisco, Francesca Arrigo, Antoine Gautier
Pubblicato in: SIAM Journal on Applied Mathematics, Numero 78/2, 2018, Pagina/e 853-876, ISSN 0036-1399
Editore: Society for Industrial and Applied Mathematics
DOI: 10.1137/17m1137668

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

Autori: Francesco Tudisco, Desmond J. Higham
Pubblicato in: SIAM Journal on Mathematics of Data Science, Numero 1/2, 2019, Pagina/e 269-292, ISSN 2577-0187
Editore: Society for Industrial and Applied Mathematics
DOI: 10.1137/18m1183558

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