Multi-Objective Population Based Training

• URL: http://arxiv.org/abs/2306.01436v1
• Date: Fri, 2 Jun 2023 10:54:24 GMT
• Title: Multi-Objective Population Based Training
• Authors: Arkadiy Dushatskiy, Alexander Chebykin, Tanja Alderliesten, Peter A.N. Bosman
• Abstract summary: Population Based Training (PBT) is an efficient hyperparameter optimization algorithm. In this work, we introduce a multi-objective version of PBT, MO-PBT.
• Score: 62.997667081978825
• License: http://creativecommons.org/licenses/by/4.0/
• 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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