Multi-fidelity Bayesian optimization in engineering design

B Do, R Zhang - arxiv preprint arxiv:2311.13050, 2023 - arxiv.org
Resided at the intersection of multi-fidelity optimization (MFO) and Bayesian optimization
(BO), MF BO has found a niche in solving expensive engineering design optimization …

Transition constrained Bayesian optimization via Markov decision processes

JP Folch, C Tsay, RM Lee, B Shafei… - arxiv preprint arxiv …, 2024 - arxiv.org
Bayesian optimization is a methodology to optimize black-box functions. Traditionally, it
focuses on the setting where you can arbitrarily query the search space. However, many real …

No-regret learning of nash equilibrium for black-box games via Gaussian processes

M Han, F Zhang, Y Chen - arxiv preprint arxiv:2405.08318, 2024 - arxiv.org
This paper investigates the challenge of learning in black-box games, where the underlying
utility function is unknown to any of the agents. While there is an extensive body of literature …

Variational Search Distributions

DM Steinberg, R Oliveira, CS Ong… - arxiv preprint arxiv …, 2024 - arxiv.org
We develop variational search distributions (VSD), a method for finding discrete,
combinatorial designs of a rare desired class in a batch sequential manner with a fixed …

Multifidelity Bayesian Optimization: A Review

B Do, R Zhang - AIAA Journal, 2023 - arc.aiaa.org
Resided at the intersection of multifidelity optimization (MFO) and Bayesian optimization
(BO), MF BO has found a niche in solving expensive engineering design optimization …

[PDF][PDF] Understanding and Improving Composite Bayesian Optimization

K Zhou, B **e, J Lyu, Z Chen - jnhujnhu.github.io
In this extended abstract, we consider Bayesian Optimization (BO) of composite objective
functions. By identifying a failure case of the existing composite BO method, we deepen the …