6 citations · 11 across the 5 of their papers we have counts for
5 papers
Sample-Efficient Bayesian Optimization with Transfer Learning for Heterogeneous Search Spaces
Aryan Deshwal, Sait Cakmak, Yuhou Xia +1
Bayesian optimization (BO) is a powerful approach to sample-efficient optimization of black-box functions. However, in settings with very few function evaluations, a successful app…
Robust Multi-Objective Bayesian Optimization Under Input Noise
Samuel Daulton, Sait Cakmak, Maximilian Balandat +3
Bayesian optimization (BO) is a sample-efficient approach for tuning design parameters to optimize expensive-to-evaluate, black-box performance metrics. In many manufacturing proce…
Contextual Ranking and Selection with Gaussian Processes
Sait Cakmak, Siyang Gao, Enlu Zhou
In many real world problems, we are faced with the problem of selecting the best among a finite number of alternatives, where the best alternative is determined based on context sp…
Solving Bayesian Risk Optimization via Nested Stochastic Gradient Estimation
Sait Cakmak, Di Wu, Enlu Zhou
In this paper, we aim to solve Bayesian Risk Optimization (BRO), which is a recently proposed framework that formulates simulation optimization under input uncertainty. In order to…
Bayesian Optimization of Risk Measures
Sait Cakmak, Raul Astudillo, Peter Frazier +1
We consider Bayesian optimization of objective functions of the form , where is a black-box expensive-to-evaluate function and denotes either the VaR or CVaR…