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math.OC2023
Regularized methods via cubic model subspace minimization for nonconvex optimization
Stefania Bellavia, Davide Palitta, Margherita Porcelli +1
Adaptive cubic regularization methods for solving nonconvex problems need the efficient computation of the trial step, involving the minimization of a cubic model. We propose a new…
math.NA2023
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…