The graph $\infty$-Laplacian eigenvalue problem

Piero Deidda, Martin Burger, Mario Putti, Francesco Tudisco
preprint, (2024)
arxiv

Cholesky-like Preconditioner for Hodge Laplacians via Heavy Collapsible Subcomplex

Anton Savostianov, Francesco Tudisco, Nicola Guglielmi
SIAM Journal on Matrix Analysis and Applications, (2024)
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

Nonlinear Spectral Duality

Francesco Tudisco, Dong Zhang
preprint, (2022)
arxiv

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

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

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

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 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

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