109 citations · 277 across the 52 of their papers we have counts for
6 papers · 1 filter
Performance comparison of optimization methods on variational quantum algorithms
Xavier Bonet-Monroig, Hao Wang, Diederick Vermetten +5
Variational quantum algorithms (VQAs) offer a promising path toward using near-term quantum hardware for applications in academic and industrial research. These algorithms aim to f…
IOHexperimenter: Benchmarking Platform for Iterative Optimization Heuristics
Jacob de Nobel, Furong Ye, Diederick Vermetten +3
We present IOHexperimenter, the experimentation module of the IOHprofiler project, which aims at providing an easy-to-use and highly customizable toolbox for benchmarking iterative…
Benchmarking the Status of Default Pseudorandom Number Generators in Common Programming Languages
Nils van den Honert, Diederick Vermetten, Anna V. Kononova
The ever-increasing need for random numbers is clear in many areas of computer science, from neural networks to optimization. As such, most common programming language provide easy…
Is there Anisotropy in Structural Bias?
Diederick Vermetten, Anna V. Kononova, Fabio Caraffini +2
Structural Bias (SB) is an important type of algorithmic deficiency within iterative optimisation heuristics. However, methods for detecting structural bias have not yet fully matu…
OPTION: OPTImization Algorithm Benchmarking ONtology
Ana Kostovska, Diederick Vermetten, Carola Doerr +3
Many platforms for benchmarking optimization algorithms offer users the possibility of sharing their experimental data with the purpose of promoting reproducible and reusable resea…
Tuning as a Means of Assessing the Benefits of New Ideas in Interplay with Existing Algorithmic Modules
Jacob de Nobel, Diederick Vermetten, Hao Wang +2
Introducing new algorithmic ideas is a key part of the continuous improvement of existing optimization algorithms. However, when introducing a new component into an existing algori…