Cholesky-like Preconditioner for Hodge Laplacians via Heavy Collapsible Subcomplex

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

A nonlinear spectral core-periphery detection method for multiplex networks

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

Quantifying the structural stability of simplicial homology

Nicola Guglielmi, Anton Savostianov, Francesco Tudisco
Journal of Scientific Computing, 97 (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

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

Nonlinear Feature Diffusion on Hypergraphs

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

Generalized matrix means for semisupervised learning with multilayer graphs

Pedro Mercado, Francesco Tudisco, Matthias Hein
In: Advances in Neural Information Processing Systems (NeurIPS), (2019)
doi arxiv poster 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)
doi code

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

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

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

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

Localization of dominant eigenpairs and planted communities by means of Frobenius inner products

Dario Fasino, Francesco Tudisco
Czechoslovak Mathematical Journal, 66 : 881--893 (2016)
doi arxiv special issue

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