In a significant development, researchers at MIT have made a breakthrough in the field of Bayesian optimization, enabling more accurate results and faster convergence for researchers using this method. This innovation comes from the Department of Electrical Engineering and Computer Science (EECS), where researchers Pulkit Agrawal, YuFeng (Kevin) Chen, Connor Coley, and Marzyeh Ghassemi have been promoted to Associate Professor Without Tenure, effective July 1, 2024.
The new technique, called constrained Bayesian optimization, is particularly useful for researchers working with Bayesian inference. It helps quantify uncertainty in their results, leading to more accurate outcomes and faster convergence.