7 papers
Iterated Tikhonov regularization of large linear problems
Davide Furchì, Lothar Reichel
Many solution methods for linear discrete ill-posed problems with error-contaminated data (right-hand side) apply Tikhonov regularization to compute a meaningful approximate soluti…
The Hermitian Distance degree of Tensor spaces
Davide Furchì
In this paper, we investigate the Hermitian distance minimization problem for determinantal varieties, the Segre variety, and the Veronese variety. In particular, for binary forms,…
The Hermitian Distance degree of an Algebraic Variety
Davide Furchì
In this paper we develop an algebraic theory to study the problem of finding the minimum distance point from an algebraic variety with respect to the Hermitian distance function. T…
The iterated Golub-Kahan-Tikhonov method
Davide Bianchi, Marco Donatelli, Davide Furchì +1
The Golub-Kahan-Tikhonov method is a popular solution technique for large linear discrete ill-posed problems. This method first applies partial Golub-Kahan bidiagonalization to red…
Improved parameter selection strategy for the iterated Arnoldi-Tikhonov method
Marco Donatelli, Davide Furchì
The iterated Arnoldi-Tikhonov (iAT) method is a regularization technique particularly suited for solving large-scale ill-posed linear inverse problems. Indeed, it reduces the compu…
Convergence analysis and parameter estimation for the iterated Arnoldi-Tikhonov method
Davide Bianchi, Marco Donatelli, Davide Furchì +1
The Arnoldi-Tikhonov method is a well-established regularization technique for solving large-scale ill-posed linear inverse problems. This method leverages the Arnoldi decompositio…