Javier González Hernández - Causal Bayesian Optimisation
日付:
2021年2月21日
著者:
Hrvoje Stojic
Causal Bayesian Optimisation: Don’t do everything, just do the right thing
Abstract
Bayesian optimization is a popular algorithm for optimizing low-dimensional functions in a data-efficient manner. In this talk, I will discuss my practical experience with Bayesian optimization when applied to robotic applications. Along this journey, I will introduce several interesting real-world problem settings that I have encountered, and the corresponding algorithms designed as a result, as well as the new insights gained. To conclude, I will briefly discuss some future challenges and potential directions.
Notes
Link to the paper: http://proceedings.mlr.press/v108/aglietti20a
Javier González Hernández is a Principal Researcher at Microsoft Research Cambridge. Personal website can be found here.
