Valeria Simoncini

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20232026

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math.NA2025

$S^{⊤} S$ -SVD via Sketching and the Nearest $S^{⊤} S$ -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 $ε$ -subspace embedding propert…

math.NA2025

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…

S⊤S-SVD via Sketching and the Nearest S⊤S-orthogonal Matrix

A subspace-conjugate gradient method for linear matrix equations

$S^{⊤} S$ -SVD via Sketching and the Nearest $S^{⊤} S$ -orthogonal Matrix