This file contains a revised version of the proofs of Theorems 3 and 4 of the paper [1]. In particular, a more correct argument is employed to obtain the inequality (A11) from (A10), provided that a stronger hypothesis on the sequence $$\{\varepsilon _k\}$$is included. The practical implementation of the algorithm (Section 3) remains as it is and all the numerical experiments (Section 4) are still valid since the stronger hypothesis on $$\{\varepsilon _k\}$$was already satisfied by the selected setting of the hyperparameters.

Correction to: A Line Search Based Proximal Stochastic Gradient Algorithm with Dynamical Variance Reduction (Journal of Scientific Computing, (2023), 94, 1, (23), 10.1007/s10915-022-02084-3)

Ruggiero V.;Trombini I.
2023

Abstract

This file contains a revised version of the proofs of Theorems 3 and 4 of the paper [1]. In particular, a more correct argument is employed to obtain the inequality (A11) from (A10), provided that a stronger hypothesis on the sequence $$\{\varepsilon _k\}$$is included. The practical implementation of the algorithm (Section 3) remains as it is and all the numerical experiments (Section 4) are still valid since the stronger hypothesis on $$\{\varepsilon _k\}$$was already satisfied by the selected setting of the hyperparameters.
2023
Franchini, G.; Porta, F.; Ruggiero, V.; Trombini, I.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11392/2517290
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