activity
20232026
most citedA multifidelity Bayesian optimization method for inertial confinement fusion design

13 citations · 14 across the 6 of their papers we have counts for

collaborators

7 papers

stat.ML2026

Practical Efficient Global Optimization is No-regret

Jingyi Wang, Haowei Wang, Nai-Yuan Chiang +3

Efficient global optimization (EGO) is one of the most widely used noise-free Bayesian optimization algorithms.It comprises the Gaussian process (GP) surrogate model and expected i…

stat.ML2025

Bayesian Optimization with Expected Improvement: No Regret and the Choice of Incumbent

Jingyi Wang, Haowei Wang, Szu Hui Ng +1

Expected improvement (EI) is one of the most widely used acquisition functions in Bayesian optimization (BO). Despite its proven empirical success in applications, the cumulative r…

stat.ML2025

Convergence Rates of Constrained Expected Improvement

Haowei Wang, Jingyi Wang, Zhongxiang Dai +3

Constrained Bayesian optimization (CBO) methods have seen significant success in black-box optimization with constraints. One of the most commonly used CBO methods is the constrain…

stat.ML2025

On the convergence rate of noisy Bayesian Optimization with Expected Improvement

Jingyi Wang, Haowei Wang, Nai-Yuan Chiang +1

Expected improvement (EI) is one of the most widely used acquisition functions in Bayesian optimization (BO). Despite its proven success in applications for decades, important open…

cs.LG2024

On Improved Regret Bounds In Bayesian Optimization with Gaussian Noise

Jingyi Wang, Haowei Wang, Cosmin G. Petra +1

Bayesian optimization (BO) with Gaussian process (GP) surrogate models is a powerful black-box optimization method. Acquisition functions are a critical part of a BO algorithm as t…

math.OC2024★ 1 cited

Constrained Bayesian optimization with merit functions

J. Wang, C. G. Petra, J. L. Peterson

Bayesian optimization is a powerful optimization tool for problems where native first-order derivatives are unavailable. Recently, constrained Bayesian optimization (CBO) has been…

physics.plasm-ph2023★ 13 cited

A multifidelity Bayesian optimization method for inertial confinement fusion design

J. Wang, N. Chiang, A. Gillette +1

Due to their cost, experiments for inertial confinement fusion (ICF) heavily rely on numerical simulations to guide design. As simulation technology progresses, so too can the fide…