Mina Konakovic Lukovic — accepted AI-conference papers

2024

Boundary Exploration for Bayesian Optimization With Unknown Physical Constraints

Yunsheng Tian, Ane Zuniga, Xinwei Zhang, Johannes P. Dürholt, Payel Das, Jie Chen +2

ICML 2024poster

Bayesian optimization has been successfully applied to optimize black-box functions where the number of evaluations is severely limited. However, in many real-world applications, it is hard or impossible to know in advance which designs are feasible due to some physical or system limitations. These…

Cited by 0 Source ↗PDF ↗code ↗Scholar ↗

2020

Diversity-Guided Multi-Objective Bayesian Optimization With Batch Evaluations

Mina Konakovic Lukovic, Yunsheng Tian, Wojciech Matusik

NeurIPS 2020poster

Many science, engineering, and design optimization problems require balancing the trade-offs between several conflicting objectives. The objectives are often black-box functions whose evaluations are time-consuming and costly. Multi-objective Bayesian optimization can be used to automate the process…

Cited by 103 Source ↗PDF ↗code ↗Scholar ↗