Bayesian tuning and bandits : an extensible, open source library for AutoML

By Laura Gustafson. 2018

11 citations recorded by the source corpus.

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

1. Marc-André Zöller
2. Marco F. Huber
3. Maryam Ashoori
4. Yufan Jiang
5. Li Yang
6. Xin He
7. Tien-Dung Nguyen

Citations in the corpus

• Benchmark and Survey of Automated Machine Learning Frameworks (2019, methodology): “BTB BTB (Gustafson, 2018) combines multi-armed bandit learning with Gaussian processes.”
• Survey on Automated Machine Learning (2019, methodology): “The cubic time complexity of Gaussian processes is clearly visible for RoBO and partially for BTB. Due to the usage of Markov chain Monte Carlo (Rubinstein and Kroese, 2008), RoBO has a significantly larger overhead.”