# PHS: A Toolbox for Parallel Hyperparameter Search

arXiv: https://arxiv.org/abs/2002.11429 · HTML: https://mlsanity.com/paper/2002.11429/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 26 Feb 2020.

## Built on by (most cited first, 1 of 1)

- [Towards Inferential Reproducibility of Machine Learning Research](https://mlsanity.com/paper/2302.04054/) (2023)

## Abstract (arXiv)

We introduce an open source python framework named PHS - Parallel Hyperparameter Search to enable hyperparameter optimization on numerous compute instances of any arbitrary python function. This is achieved with minimal modifications inside the target function. Possible applications appear in expensive to evaluate numerical computations which strongly depend on hyperparameters such as machine learning. Bayesian optimization is chosen as a sample efficient method to propose the next query set of parameters.