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Poster
ChaCha for Online AutoML
Qingyun Wu · Chi Wang · John Langford · Paul Mineiro · Marco Rossi

Wed Jul 21 09:00 AM -- 11:00 AM (PDT) @
in Poster Session 3 »

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.

Keywords: Algorithms · Online Learning Algorithms

Author Information

Qingyun Wu (Microsoft Research)
Chi Wang (Microsoft Research)
John Langford (Microsoft Research)
Paul Mineiro (Microsoft)
Marco Rossi (Microsoft Corporation)

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