20 citations · 51 across the 8 of their papers we have counts for
4 papers · 1 filter
Sampling from Gaussian Processes: A Tutorial and Applications in Global Sensitivity Analysis and Optimization
Bach Do, Nafeezat A. Ajenifuja, Taiwo A. Adebiyi +1
High-fidelity simulations and physical experiments are essential for engineering analysis and design, yet their high cost often makes two critical tasks--global sensitivity analysi…
Gaussian Process Thompson Sampling via Rootfinding
Taiwo A. Adebiyi, Bach Do, Ruda Zhang
Thompson sampling (TS) is a simple, effective stochastic policy in Bayesian decision making. It samples the posterior belief about the reward profile and optimizes the sample to ob…
Optimizing Posterior Samples for Bayesian Optimization via Rootfinding
Taiwo A. Adebiyi, Bach Do, Ruda Zhang
Bayesian optimization devolves the global optimization of a costly objective function to the global optimization of a sequence of acquisition functions. This inner-loop optimizatio…
Epsilon-Greedy Thompson Sampling to Bayesian Optimization
Bach Do, Taiwo Adebiyi, Ruda Zhang
Bayesian optimization (BO) has become a powerful tool for solving simulation-based engineering optimization problems thanks to its ability to integrate physical and mathematical un…