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math.NA2025
An Additively Preconditioned Trust Region Strategy for Machine Learning
Samuel Cruz Alegría, Bindi Çapriqi, Shega Likaj +2
Modern machine learning, especially the training of deep neural networks, depends on solving large-scale, highly nonconvex optimization problems, whose objective function exhibit a…
cs.LG2025
Data-Parallel Neural Network Training via Nonlinearly Preconditioned Trust-Region Method
Samuel A. Cruz Alegría, Ken Trotti, Alena Kopaničáková +1
Parallel training methods are increasingly relevant in machine learning (ML) due to the continuing growth in model and dataset sizes. We propose a variant of the Additively Precond…