The repository contains the source code of the paper "An adaptive memory multi-batch L-BFGS algorithm for neural network training" authored by Federico Zocco and Seán McLoone. The paper has been presented at the 21st IFAC World Congress, held in Berlin in July 12-17, 2020.
If you use the code, please consider citing the corresponding paper: Federico Zocco, Seán McLoone, An Adaptive Memory Multi-Batch L-BFGS Algorithm for Neural Network Training, IFAC-PapersOnLine, Volume 53, Issue 2, 2020, Pages 8199-8204, ISSN 2405-8963, https://doi.org/10.1016/j.ifacol.2020.12.1996.
Note that the datasets are not uploaded in this folder because too large. See Table 1 of my paper if you need information to find the datasets.
The script "Algorithms_comparison.py" should be executed by the user to do the Monte Carlo simulations that compare the training algorithms on different datasets. It uses all the modules inside the same folder of "Algorithms_comparison.py". It also uses the modules inside the folder "functions".
The datasets for Experiments 1, 4 and 5 are downloaded by "Algorithms_comparison.py" from the Internet.
The folder "Others" contains 2 scripts demonstrating how to do image rescaling and data augmentation. They are not used by the script "Algorithms_comparison.py". I have created and used this 2 scripts to rescale and augment the datasets as detailed in my paper.