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arXiv · 2106.04815

ChaCha for Online AutoML

Qingyun Wu·Chi Wang·John Langford·Paul Mineiro·Marco Rossi
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Abstract

We propose the ChaCha (Champion-Challengers) algorithm for making an online choice of hyperparameters in online learning settings. ChaCha handles the process of determining a champion and scheduling a set of `live' challengers over time based on sample complexity bounds. It is guaranteed to have sublinear regret after the optimal configuration is added into consideration by an application-dependent oracle based on the champions. Empirically, we show that ChaCha provides good performance across a wide array of datasets when optimizing over featurization and hyperparameter decisions.

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Qingyun Wu, Chi Wang, John Langford, Paul Mineiro, Marco Rossi. 2021-06-09. ChaCha for Online AutoML. https://arxiv.org/abs/2106.04815

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