4 papers
Randomized Tucker-Sketched GMRES
Alberto Bucci, Martina Iannacito, Mirjeta Pasha +1
We address the problem of solving large-scale tensor-structured linear systems in the Tucker format. In this setting, standard iterative solvers such as GMRES face a fundamental bo…
A Practical Mode-parallel Implementation of the (H-)Tucker Decomposition via Randomization
Martina Iannacito, Sascha Portaro, Davide Palitta +2
In the last decades, tensors have emerged as the right tool to represent multidimensional data in a compact yet informative manner. Moreover, it is well-known that by performing lo…
Subspace gradient descent method for linear tensor equations
Martina Iannacito, Lorenzo Piccinini, Valeria Simoncini
The numerical solution of algebraic tensor equations is a largely open and challenging task. Assuming that the operator is symmetric and positive definite, we propose two new gradi…
A subspace-conjugate gradient method for linear matrix equations
Davide Palitta, Martina Iannacito, Valeria Simoncini
The efficient solution of large-scale multiterm linear matrix equations is a challenging task in numerical linear algebra, and it is a largely open problem. We propose a new iterat…