18 citations · 22 across the 2 of their papers we have counts for
3 papers
cs.SC2020★ 4 cited
A machine learning based software pipeline to pick the variable ordering for algorithms with polynomial inputs
Dorian Florescu, Matthew England
We are interested in the application of Machine Learning (ML) technology to improve mathematical software. It may seem that the probabilistic nature of ML tools would invalidate th…
cs.SC2019
Improved cross-validation for classifiers that make algorithmic choices to minimise runtime without compromising output correctness
Dorian Florescu, Matthew England
Our topic is the use of machine learning to improve software by making choices which do not compromise the correctness of the output, but do affect the time taken to produce such o…
cs.SC2019★ 18 cited
Comparing machine learning models to choose the variable ordering for cylindrical algebraic decomposition
Matthew England, Dorian Florescu
There has been recent interest in the use of machine learning (ML) approaches within mathematical software to make choices that impact on the computing performance without affectin…