# Adaptive Optimizer for Automated Hyperparameter Optimization Problem

arXiv: https://arxiv.org/abs/2201.12124 · HTML: https://mlsanity.com/paper/2201.12124/

## Key facts

- No citing papers in the map yet (data through 14 Oct 2026).
- Builds on 0 of its 5 references that are in the map.
- First posted on arXiv 28 Jan 2022.

## Abstract (arXiv)

The choices of hyperparameters have critical effects on the performance of machine learning models. In this paper, we present a general framework that is able to construct an adaptive optimizer, which automatically adjust the appropriate algorithm and parameters in the process of optimization. Examining the method of adaptive optimizer, we product an example of using genetic algorithm to construct an adaptive optimizer based on Bayesian Optimizer and compared effectiveness with original optimizer. Especially, It has great advantages in parallel optimization.