ChaCha for Online AutoML
2021-06-09Code Available2· sign in to hype
Qingyun Wu, Chi Wang, John Langford, Paul Mineiro, Marco Rossi
Code Available — Be the first to reproduce this paper.
ReproduceCode
- github.com/microsoft/FLAMLOfficialIn papernone★ 4,306
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.