Francesco Tudisco

Associate Professor (Reader) in Machine Learning

School of Mathematics, The University of Edinburgh
The Maxwell Institute for Mathematical Sciences
School of Mathematics, Gran Sasso Science Institute JCMB, King’s Buildings, Edinburgh EH93FD UK
email: f dot tudisco at ed.ac.uk

Keyword: Networks

Cholesky-like Preconditioner for Hodge Laplacians via Heavy Collapsible Subcomplex

Anton Savostianov, Francesco Tudisco, Nicola Guglielmi
preprint, (2024)
arxiv doi code

Collaboration and topic switches in science

Sara Venturini, Satyaki Sikdar, Francesco Rinaldi, Francesco Tudisco, Santo Fortunato
Scientific Reports, 14 : 1258 (2024)
doi arxiv code

A nonlinear spectral core-periphery detection method for multiplex networks

Kai Bergermann, Martin Stoll, Francesco Tudisco
preprint, (2024)
arxiv code

Learning the effective order of a hypergraph dynamical system

Leonie Neuhäuser, Michael Scholkemper, Francesco Tudisco, Michael T. Schaub
Science Advances, (2024)
arxiv doi code

Optimizing network robustness via Krylov subspaces

Stefano Massei, Francesco Tudisco
ESAIM: Mathematical Modelling and Numerical Analysis, (2024)
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Laplacian-based Semi-Supervised Learning in Multilayer Hypergraphs by Coordinate Descent

Sara Venturini, Andrea Cristofari, Francesco Rinaldi, Francesco Tudisco
EURO Journal on Computational Optimization, (2023)
arxiv doi code

Quantifying the structural stability of simplicial homology

Nicola Guglielmi, Anton Savostianov, Francesco Tudisco
Journal of Scientific Computing, 97 (2023)
arxiv doi code

A Variance-aware Multiobjective Louvain-like Method for Community Detection in Multiplex Networks

Sara Venturini, Andrea Cristofari, Francesco Rinaldi, Francesco Tudisco
Journal of Complex Networks, (2022)
arxiv doi code

Learning the right layers: a data-driven layer-aggregation strategy for semi-supervised learning on multilayer graphs

Sara Venturini, Andrea Cristofari, Francesco Rinaldi, Francesco Tudisco
In: International Conference on Machine Learning (ICML), (2023)
arxiv doi code

Core-periphery detection in hypergraphs

Francesco Tudisco, Desmond J. Higham
SIAM Journal on Mathematics of Data Science, 5 (2023)
doi arxiv code

Core-periphery partitioning and quantum annealing

Catherine F. Higham, Desmond J. Higham, Francesco Tudisco
In: ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD), (2022)
arxiv doi

Nodal domain count for the generalized graph $p$-Laplacian

Piero Deidda, Mario Putti, Francesco Tudisco
Applied and Computational Harmonic Analysis, 64 : 1--32 (2023)
arxiv doi

The self-consistent field iteration for p-spectral clustering

Parikshit Upadhyaya, Elias Jarlebring, Francesco Tudisco
preprint, (2021)
arxiv

Hitting times for second-order random walks

Dario Fasino, Arianna Tonetto, Francesco Tudisco
European Journal of Applied Mathematics, 34 : 642--666 (2022)
arxiv doi

Nonlinear Feature Diffusion on Hypergraphs

Konstantin Prokopchik, Austin R. Benson, Francesco Tudisco
In: International Conference of Machine Learning (ICML), (2022)
arxiv doi code

Node and Edge Eigenvector Centrality for Hypergraphs

Francesco Tudisco, Desmond J. Higham
Communications Physics, 4:201 (2021)
doi-open arxiv code

Nonlinear Higher-Order Label Spreading

Francesco Tudisco, Austin R. Benson, Konstantin Prokopchik
In: Proceedings of The Web Conference, : 2402--2413 (2021)
doi arxiv code

Nonlocal PageRank

Stefano Cipolla, Fabio Durastante, Francesco Tudisco
ESAIM Mathematical Modelling and Numerical Analysis, 55 : 77--97 (2021)
doi arxiv code

A framework for second order eigenvector centralities and clustering coefficients

Francesca Arrigo, Desmond J. Higham, Francesco Tudisco
Proceedings Royal Society A, 476 : 20190724 (2020)
arxiv doi-open code

Generating large scale-free networks with the Chung-Lu random graph model

Dario Fasino, Arianna Tonetto, Francesco Tudisco
Networks, (2020)
doi arxiv code

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

Francesco Tudisco, Desmond J. Higham
Applied Network Science, 4 : 1--13 (2019)
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Spectral Clustering of Signed Graphs via Matrix Power Means

Pedro Mercado, Francesco Tudisco, Matthias Hein
In: International Conference on Machine Learning (ICML), : 4526--4536 (2019)
doi arxiv

Multi-Dimensional, Multilayer, Nonlinear and Dynamic HITS

Francesca Arrigo, Francesco Tudisco
In: SIAM International Conference on Data Mining, : 369--377 (2019)
doi arxiv code

A nonlinear spectral method for core-periphery detection in networks

Francesco Tudisco, Desmond J. Higham
SIAM J. Mathematics of Data Science, 1 : 269--292 (2019)
doi arxiv code

The Power Mean Laplacian for Multilayer Graph Clustering

Pedro Mercado, Antoine Gautier, Francesco Tudisco, Matthias Hein
In: International Conference on Artificial Intelligence and Statistics (AISTATS), Proc. Machine Learning Research, 84 : 1828--1838 (2018)
doi arxiv code

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

Dario Fasino, Francesco Tudisco
Special Matrices, 6 : 110--121 (2018)
doi

Node and layer eigenvector centralities for multiplex networks

Francesco Tudisco, Francesca Arrigo, Antoine Gautier
SIAM J. Applied Mathematics, 78 : 853--876 (2018)
doi arxiv code

A modularity based spectral method for simultaneous community and anti-community detection

Dario Fasino, Francesco Tudisco
Linear Algebra and its Applications, 542 : 605--623 (2018)
doi arxiv

On the stability of network indices defined by means of matrix functions

Stefano Pozza, Francesco Tudisco
SIAM J. Matrix Analysis Appl., 39 : 1521--1546 (2018)
doi arxiv

Community detection in networks via nonlinear modularity eigenvectors

Francesco Tudisco, Pedro Mercado, Matthias Hein
SIAM J. Applied Mathematics, 78 : 2393--2419 (2018)
doi arxiv

A nodal domain theorem and a higher-order Cheeger inequality for the graph p-Laplacian

Francesco Tudisco, Matthias Hein
EMS Journal of Spectral Theory, 8 : 883--908 (2018)
doi arxiv

Generalized modularity matrices

Dario Fasino, Francesco Tudisco
Linear Algebra and its Applications, 502 : 327--345 (2016)
doi arxiv

Clustering Signed Networks with the Geometric Mean of Laplacians

Pedro Mercado, Francesco Tudisco, Matthias Hein
In: Advances in Neural Information Processing Systems 29 (NeurIPS), (2016)
nips code

An algebraic analysis of the graph modularity

Dario Fasino, Francesco Tudisco
SIAM J. Matrix Analysis and Applications, 35 : 997--1018 (2014)
doi arxiv