6 papers · 1 filter
A class of low-rank short recurrences for nonsymmetric linear matrix equations
Davide Palitta, Catherine E. Powell, Valeria Simoncini
We propose a new class of short matrix recurrences for the solution of nonsymmetric linear equations of the type $\mathbf{A}_1\mathbf{X}\mathbf{B}_1+\ldots+\mathbf{A}_p\mathbf{X}\m…
-SVD via Sketching and the Nearest -orthogonal Matrix
Davide Palitta, Valeria Simoncini
Sketching techniques have gained popularity in numerical linear algebra to accelerate the solution of least squares problems. The so-called -subspace embedding propert…
Row-aware Randomized SVD with applications
Davide Palitta, Sascha Portaro
The randomized singular value decomposition proposed in [27] has certainly become one of the most well-established randomization-based algorithms in numerical linear algebra. The k…
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…
Sketched and truncated polynomial Krylov methods: Evaluation of matrix functions
Davide Palitta, Marcel Schweitzer, Valeria Simoncini
Among randomized numerical linear algebra strategies, so-called sketching procedures are emerging as effective reduction means to accelerate the computation of Krylov subspace meth…
Sketched and Truncated Polynomial Krylov Subspace Methods: Matrix Sylvester Equations
Davide Palitta, Marcel Schweitzer, Valeria Simoncini
Thanks to its great potential in reducing both computational cost and memory requirements, combining sketching and Krylov subspace techniques has attracted a lot of attention in th…