Bayesian optimization is a methodology for sample-efficient learning and optimization. By leveraging a probabilistic model, it allows practitioners and researchers to explore large design spaces using only a small number of experimental trials. At Facebook, we utilize Bayesian optimization to improve product experiences, infrastructure, and aid in cutting edge research. For example, Bayesian optimization may be used to learn personalized video playback algorithms that work well across a diverse set of devices and levels of connectivity. Machine learning teams like Instagram Feed & Stories Relevance use Bayesian optimization to refine their latest machine learning models through the use of online A/B tests. And teams at Facebook Reality Lab use Bayesian optimization to efficiently conduct research in the area of perception in only a fraction of the time that conventional experiments would require.
To enable and support this work, we developed and open-sourced BoTorch, a modular framework for Bayesian optimization research, and Ax, a turn-key framework for those who want to apply Bayesian optimization to their own problems. Our goal with BoTorch is to accelerate the pace of research in the area of Bayesian optimization and unlock new potential applications. With this RFP, we hope to deepen our ties to the academic research community by seeking out innovative ideas and applications of Bayesian optimization that further advance the field. We are committed to open source and will help awardees make the products of this RFP available to the public as part of BoTorch.
Facebook is pleased to invite faculty to respond to this call for research proposals. In order to support academic work that addresses our challenges and opportunities while producing generalizable knowledge, Facebook is pleased to offer two research awards of $50,000 and $25,000, respectively. Awards will be made as unrestricted gifts to the principal investigator’s host university. Awardees will be invited to present and engage in discussion with researchers at Facebook.