Corpus ID: 80628408

Tuning Hyperparameters without Grad Students: Scalable and Robust Bayesian Optimisation with Dragonfly

@article{Kandasamy2019TuningHW,
  title={Tuning Hyperparameters without Grad Students: Scalable and Robust Bayesian Optimisation with Dragonfly},
  author={Kirthevasan Kandasamy and Karun Raju Vysyaraju and W. Neiswanger and Biswajit Paria and C. Collins and Jeff Schneider and B. P{\'o}czos and E. Xing},
  journal={ArXiv},
  year={2019},
  volume={abs/1903.06694}
}
  • Kirthevasan Kandasamy, Karun Raju Vysyaraju, +5 authors E. Xing
  • Published 2019
  • Computer Science, Mathematics
  • ArXiv
  • Bayesian Optimisation (BO), refers to a suite of techniques for global optimisation of expensive black box functions, which use introspective Bayesian models of the function to efficiently find the optimum. While BO has been applied successfully in many applications, modern optimisation tasks usher in new challenges where conventional methods fail spectacularly. In this work, we present Dragonfly, an open source Python library for scalable and robust BO. Dragonfly incorporates multiple recently… CONTINUE READING
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