Date of Award
12-17-2022
Document Type
Masters Project
Abstract
When dealing with sufficiently large integers, even the most cutting-edge existing algorithms for computing prime factorizations are impractically slow. In this paper, we explore the possibility of using neural networks to approximate prime factorizations in the hopes of providing an alternative factorization method which trades accuracy for speed. Due to the intrinsic difficulty associated with this task, the focus of this paper is largely concentrated on the obstacles encountered in the training of the neural net, rather than on the viability of the method itself.
Recommended Citation
Dragomir, Dakota, "Computing prime factorizations with neural networks" (2022). Mathematics and Statistics . 61.
https://ualaska.researchcommons.org/uaf_grad_math_stats/61
Handle
http://hdl.handle.net/11122/14732