
Hitting times for nonbacktracking random walks
A nonbacktracking random walk on a graph is a random walk where, at eac...
read it

A nonlinear diffusion method for semisupervised learning on hypergraphs
Hypergraphs are a common model for multiway relationships in data, and h...
read it

Node and Edge Eigenvector Centrality for Hypergraphs
Network scientists have shown that there is great value in studying pair...
read it

Nonlinear HigherOrder Label Spreading
Label spreading is a general technique for semisupervised learning with...
read it

Computing the norm of nonnegative matrices and the logSobolev constant of Markov chains
We analyze the global convergence of the power iterates for the computat...
read it

Nonlocal PageRank
In this work we introduce and study a nonlocal version of the PageRank. ...
read it

Generalized Matrix Means for SemiSupervised Learning with Multilayer Graphs
We study the task of semisupervised learning on multilayer graphs by ta...
read it

A framework for second order eigenvector centralities and clustering coefficients
We propose and analyse a general tensorbased framework for incorporatin...
read it

Shifted and extrapolated power methods for tensor ℓ^peigenpairs
This work is concerned with the computation of ℓ^peigenvalues and eigen...
read it

Higherorder ergodicity coefficients for stochastic tensors
Ergodicity coefficients for stochastic matrices provide valuable upper b...
read it

Higherorder ergodicity coefficients
Ergodicity coefficients for stochastic matrices provide valuable upper b...
read it

Spectral Clustering of Signed Graphs via Matrix Power Means
Signed graphs encode positive (attractive) and negative (repulsive) rela...
read it

MultiDimensional, Multilayer, Nonlinear and Dynamic HITS
We introduce a ranking model for temporal multidimensional weighted and...
read it

The Power Mean Laplacian for Multilayer Graph Clustering
Multilayer graphs encode different kind of interactions between the same...
read it

A unifying PerronFrobenius theorem for nonnegative tensors via multihomogeneous maps
Inspired by the definition of symmetric decomposition, we introduce the ...
read it

On the stability of network indices defined by means of matrix functions
Identifying important components in a network is one of the major goals ...
read it

Community detection in networks via nonlinear modularity eigenvectors
Revealing a community structure in a network or dataset is a central pro...
read it

Clustering Signed Networks with the Geometric Mean of Laplacians
Signed networks allow to model positive and negative relationships. We a...
read it

An Efficient Multilinear Optimization Framework for Hypergraph Matching
Hypergraph matching has recently become a popular approach for solving c...
read it
Francesco Tudisco
is this you? claim profile