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arXiv · 2306.01436

Multi-Objective Population Based Training

Arkadiy Dushatskiy·Alexander Chebykin·Tanja Alderliesten·Peter A. N. Bosman
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Abstract

Population Based Training (PBT) is an efficient hyperparameter optimization algorithm. PBT is a single-objective algorithm, but many real-world hyperparameter optimization problems involve two or more conflicting objectives. In this work, we therefore introduce a multi-objective version of PBT, MO-PBT. Our experiments on diverse multi-objective hyperparameter optimization problems (Precision/Recall, Accuracy/Fairness, Accuracy/Adversarial Robustness) show that MO-PBT outperforms random search, single-objective PBT, and the state-of-the-art multi-objective hyperparameter optimization algorithm MO-ASHA.

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Arkadiy Dushatskiy, Alexander Chebykin, Tanja Alderliesten, Peter A. N. Bosman. 2023-06-02. Multi-Objective Population Based Training. https://arxiv.org/abs/2306.01436

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