4 papers
Cost-aware Stopping for Bayesian Optimization
Qian Xie, Linda Cai, Alexander Terenin +2
In automated machine learning, scientific discovery, and other applications of Bayesian optimization, deciding when to stop evaluating expensive black-box functions in a cost-aware…
The Gittins Index: A Design Principle for Decision-Making Under Uncertainty
Ziv Scully, Alexander Terenin
The Gittins index is a tool that optimally solves a variety of decision-making problems involving uncertainty, including multi-armed bandit problems, minimizing mean latency in que…
Local hedging approximately solves Pandora's box problems with nonobligatory inspection
Ziv Scully, Laura Doval
We consider search problems with nonobligatory inspection and single-item or combinatorial selection. A decision maker is presented with a number of items, each of which contains a…
Cost-aware Bayesian Optimization via the Pandora's Box Gittins Index
Qian Xie, Raul Astudillo, Peter I. Frazier +2
Bayesian optimization is a technique for efficiently optimizing unknown functions in a black-box manner. To handle practical settings where gathering data requires use of finite re…