2 papers
math.OC2026
A Non-Monotone Preconditioned Trust-Region Method for Neural Network Training
Andrea Angino, Bindi Ãapriqi, Shega Likaj +2
Training deep neural networks at scale can benefit from domain decomposition, where the network is split into subdomains trained in parallel and coupled by a global trust-region me…
math.NA2025
An Additively Preconditioned Trust Region Strategy for Machine Learning
Samuel Cruz AlegrÃa, Bindi Ãapriqi, 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…