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arXiv · 2404.13382

An investigation of stochastic trust-region based algorithms for finite-sum minimization

Stefania Bellavia·Benedetta Morini·Simone Rebegoldi
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Abstract

This work elaborates on the TRust-region-ish (TRish) algorithm, a stochastic optimization method for finite-sum minimization problems proposed by Curtis et al. in [Curtis2019, Curtis2022]. A theoretical analysis that complements the results in the literature is presented, and the issue of tuning the involved hyper-parameters is investigated. Our study also focuses on a practical version of the method, which computes the stochastic gradient by means of the inner product test and the orthogonality test proposed by Bollapragada et al. in [Bollapragada2018]. It is shown experimentally that this implementation improves the performance of TRish and reduces its sensitivity to the choice of the hyper-parameters.

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Stefania Bellavia, Benedetta Morini, Simone Rebegoldi. 2024-04-20. An investigation of stochastic trust-region based algorithms for finite-sum minimization. https://arxiv.org/abs/2404.13382

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