XOR_p A maximally intertwined p-classes problem used as a benchmark with built-in truth for neural networks gradient descent optimization
Machine Learning
2018-12-19 v1 Machine Learning
Abstract
A natural p-classes generalization of the eXclusive OR problem, the subtraction modulo p, where p is prime, is presented and solved using a single fully connected hidden layer with p-neurons. Although the problem is very simple, the landscape is intricate and challenging and represents an interesting benchmark for gradient descent optimization algorithms. Testing 9 optimizers and 9 activation functions up to p = 191, the method converging most often and the fastest to a perfect classification is the Adam optimizer combined with the ELU activation function.
Cite
@article{arxiv.1812.07538,
title = {XOR_p A maximally intertwined p-classes problem used as a benchmark with built-in truth for neural networks gradient descent optimization},
author = {Danielle Thierry-Mieg and Jean Thierry-Mieg},
journal= {arXiv preprint arXiv:1812.07538},
year = {2018}
}
Comments
16 pages, 4 figures, 3 tables. The source code is public