In this paper, we investigate the influence of noise giving an estimate of the gradient having a acute angle with the original. Noise amplitude has a relative model. The work offers both theoretical calculations and theorems, as well as experimental results. Classic machine learning problems were chosen as experiments -- linear and logistic regression, computer vision and natural language processing.
@article{arxiv.2407.00667,
title = {Gradient directions and relative inexactness in optimization and machine learning},
author = {Artem Vasin},
journal= {arXiv preprint arXiv:2407.00667},
year = {2024}
}