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  • title: Multi-objective Tree-structured Parzen Estimator Meets Meta-learning
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            Multi-objective Tree-structured Parzen Estimator Meets Meta-learning
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            Multi-objective Tree-structured Parzen Estimator Meets Meta-learning

            Dec 2, 2022

            Speakers

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            Shuhei Watanabe

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            Noor Awad

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            MO

            Masaki Onishi

            Speaker · 0 followers

            About

            Hyperparameter optimization (HPO) is essential for the better performance of deep learning, and practitioners often need to consider the trade-off between multiple metrics, such as error rate, latency, memory requirements, robustness, and algorithmic fairness. Due to this demand and the heavy computation of deep learning, the acceleration of multi-objective (MO) optimization becomes ever more important. Although meta-learning has been extensively studied to speedup HPO, existing methods are not…

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            NeurIPS 2022

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