Abstract This package provides a meta-learning extension of the Tree-structured Parzen Estimator (TPE) that leverages previously completed Optuna studies on related tasks to accelerate optimization.
The algorithm is based on the approach described in:
Speeding Up Multi-Objective Hyperparameter Optimization by Task Similarity-Based Meta-Learning for the Tree-Structured Parzen Estimator (IJCAI 2023) The key idea is to compute task similarity between the target task and source tasks based on the overlap of their promising regions, and then use a weighted mixture of TPE models to guide the search.