1 citations · 1 across the 7 of their papers we have counts for
10 papers
Sampling in CMA-ES: Low Numbers of Low Discrepancy Points
Jacob de Nobel, Diederick Vermetten, Thomas H. W. Bäck +1
The Covariance Matrix Adaptation Evolution Strategy (CMA-ES) is one of the most successful examples of a derandomized evolution strategy. However, it still relies on randomly sampl…
Avoiding Redundant Restarts in Multimodal Global Optimization
Jacob de Nobel, Diederick Vermetten, Anna V. Kononova +2
Naïve restarts of global optimization solvers when operating on multimodal search landscapes may resemble the Coupon's Collector Problem, with a potential to waste significant func…
BBOB Instance Analysis: Landscape Properties and Algorithm Performance across Problem Instances
Fu Xing Long, Diederick Vermetten, Bas van Stein +1
Benchmarking is a key aspect of research into optimization algorithms, and as such the way in which the most popular benchmark suites are designed implicitly guides some parts of a…
Optimizing Stimulus Energy for Cochlear Implants with a Machine Learning Model of the Auditory Nerve
Jacob de Nobel, Anna V. Kononova, Jeroen Briaire +2
Performing simulations with a realistic biophysical auditory nerve fiber model can be very time consuming, due to the complex nature of the calculations involved. Here, a surrogate…
Using Machine Learning to Detect Rotational Symmetries from Reflectional Symmetries in 2D Images
Koen Ponse, Anna V. Kononova, Maria Loleyt +1
Automated symmetry detection is still a difficult task in 2021. However, it has applications in computer vision, and it also plays an important part in understanding art. This pape…
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…