Empirical study towards understanding line search approximations for training neural networks. - Younghwan Chae; Daniel N. Wilke (CoRR, 2019)

GOALS: Gradient-Only Approximations for Line Searches Towards Robust and Consistent Training of Deep Neural Networks. - Younghwan Chae; Daniel N. Wilke; Dominic Kafka (CoRR, 2021)

Gradient-only surrogate to resolve learning rates for robust and consistent training of deep neural networks. - Younghwan Chae; Daniel N. Wilke; Dominic Kafka (Appl. Intell., 2023)