Robust Bayesian Optimization

Robust Bayesian Optimization (BO) aims to efficiently find optimal solutions for complex, noisy, or uncertain systems, addressing limitations of standard BO methods. Current research focuses on developing algorithms that handle input uncertainty (e.g., AIRBO using Maximum Mean Discrepancy), improve acquisition function design for better exploration-exploitation balance (e.g., self-adjusting acquisition functions), and account for model imprecision (e.g., by incorporating prior uncertainty). These advancements enhance the reliability and efficiency of BO across diverse applications, from engineering design to materials science, where robustness to noise and uncertainty is crucial.

Papers

March 6, 2024

Targeted Variance Reduction: Robust Bayesian Optimization of Black-Box Simulators with Noise Parameters
John Joshua Miller, Simon Mak
Optimization Purpose Robust Optimization Variance Reduction Noise Estimation Robust Performance Stochastic Robust Optimization Robust Bayesian Optimization

October 31, 2023

Efficient Robust Bayesian Optimization for Arbitrary Uncertain Inputs
Lin Yang, Junlong Lyu, Wenlong Lyu, Zhitang Chen
Bayesian Optimization Sample Efficient Input Uncertainty Stochastic Robust Optimization Robust Bayesian Optimization

June 7, 2023

Self-Adjusting Weighted Expected Improvement for Bayesian Optimization
Carolin Benjamins, Elena Raponi, Anja Jankovic, Carola Doerr, Marius Lindauer
Bayesian Optimization Surrogate Model Large Relevance Improvement Adaptive Weight Expected Improvement Robust Bayesian Optimization

October 2, 2022

Robust Bayesian optimization with reinforcement learned acquisition functions
Zijing Liu, Xiyao Qu, Xuejun Liu, Hongqiang Lyu
Markov Decision Process Bayesian Optimization Positive Reinforcement Efficient Optimization Acquisition Function Acquisition Model Robust Bayesian Optimization

March 4, 2022

Distributionally Robust Bayesian Optimization with $\varphi$-divergences
Hisham Husain, Vu Nguyen, Anton van den Hengel
Native Robustness Bayesian Optimization Sublinear Regret Distributionally Robust Optimization Divergence Regularization Robust Bayesian Optimization

February 11, 2022

Uncertainty Aware System Identification with Universal Policies
Buddhika Laknath Semage, Thommen George Karimpanal, Santu Rana, Svetha Venkatesh
Reinforcement Learning Robust Policy Domain Randomization Uncertain System Trained Policy Robust Bayesian Optimization

November 16, 2021

Accounting for Gaussian Process Imprecision in Bayesian Optimization
Julian Rodemann, Thomas Augustin
Gaussian Process Bayesian Optimization Surrogate Model Uncertainty Propagation Robust Bayesian Optimization