ChaCha for Online AutoML - Wu, Qingyun; Wang, Chi; Langford, John; Mineiro, Paul; Rossi, Marco (2021 International Conference on Machine Learning (ICML 2021), 2021)
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.