1 code implementation • 16 May 2024 • Christian Internò, Elena Raponi, Niki van Stein, Thomas Bäck, Markus Olhofer, Yaochu Jin, Barbara Hammer
However, its application on edge devices is hindered by limited computational capabilities and data communication challenges, compounded by the inherent complexity of Deep Learning (DL) models.
no code implementations • 29 Sep 2023 • Elena Raponi, Nathanael Rakotonirina Carraz, Jérémy Rapin, Carola Doerr, Olivier Teytaud
BO-based algorithms are popular in the ML community, as they are used for hyperparameter optimization and more generally for algorithm configuration.
1 code implementation • 7 Jun 2023 • Carolin Benjamins, Elena Raponi, Anja Jankovic, Carola Doerr, Marius Lindauer
Bayesian Optimization (BO) is a class of surrogate-based, sample-efficient algorithms for optimizing black-box problems with small evaluation budgets.
1 code implementation • 2 Mar 2023 • Maria Laura Santoni, Elena Raponi, Renato De Leone, Carola Doerr
Bayesian Optimization (BO) is a class of black-box, surrogate-based heuristics that can efficiently optimize problems that are expensive to evaluate, and hence admit only small evaluation budgets.
1 code implementation • 17 Nov 2022 • Carolin Benjamins, Anja Jankovic, Elena Raponi, Koen van der Blom, Marius Lindauer, Carola Doerr
Bayesian optimization (BO) algorithms form a class of surrogate-based heuristics, aimed at efficiently computing high-quality solutions for numerical black-box optimization problems.
1 code implementation • 2 Nov 2022 • Carolin Benjamins, Elena Raponi, Anja Jankovic, Koen van der Blom, Maria Laura Santoni, Marius Lindauer, Carola Doerr
We also compare this to a random schedule and round-robin selection of EI and PI.
no code implementations • 28 Apr 2022 • Kirill Antonov, Elena Raponi, Hao Wang, Carola Doerr
Bayesian Optimization (BO) is a surrogate-based global optimization strategy that relies on a Gaussian Process regression (GPR) model to approximate the objective function and an acquisition function to suggest candidate points.
no code implementations • 29 Sep 2021 • Elena Raponi, Nathanaël Carraz Rakotonirina, Jérémy Rapin, Olivier Teytaud, Carola Doerr
Machine learning has invaded various domains of computer science, including black-box optimization.
1 code implementation • 2 Jul 2020 • Elena Raponi, Hao Wang, Mariusz Bujny, Simonetta Boria, Carola Doerr
Bayesian Optimization (BO) is a surrogate-assisted global optimization technique that has been successfully applied in various fields, e. g., automated machine learning and design optimization.