7 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…
On some orthogonalization schemes in Tensor Train format
Olivier Coulaud, Luc Giraud, Martina Iannacito
In the framework of tensor spaces, we consider orthogonalization kernels to generate an orthogonal basis of a tensor subspace from a set of linearly independent tensors. In particu…
A robust GMRES algorithm in Tensor Train format
Olivier Coulaud, Luc Giraud, Martina Iannacito
We consider the solution of linear systems with tensor product structure using a GMRES algorithm. In order to cope with the computational complexity in large dimension both in term…
Extension of Correspondence Analysis to multiway data-sets through High Order SVD: a geometric framework
Olivier Coulaud, Alain Franc, Martina Iannacito
This paper presents an extension of Correspondence Analysis (CA) to tensors through High Order Singular Value Decomposition (HOSVD) from a geometric viewpoint. Correspondence analy…