activity
20192021
most citedLearning adaptive differential evolution algorithm from optimization experiences by policy gradient

4 citations · 4 across the 1 of their papers we have counts for

collaborators

5 papers

stat.ME2021

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…

cs.NE20214 cited

Learning adaptive differential evolution algorithm from optimization experiences by policy gradient

Jianyong Sun, Xin Liu, Thomas Bäck +1

Differential evolution is one of the most prestigious population-based stochastic optimization algorithm for black-box problems. The performance of a differential evolution algorit…

quant-ph2020

Tabu-driven Quantum Neighborhood Samplers

Charles Moussa, Hao Wang, Henri Calandra +2

Combinatorial optimization is an important application targeted by quantum computing. However, near-term hardware constraints make quantum algorithms unlikely to be competitive whe…

cs.LG2020

Neural Network Design: Learning from Neural Architecture Search

Bas van Stein, Hao Wang, Thomas Bäck

Neural Architecture Search (NAS) aims to optimize deep neural networks' architecture for better accuracy or smaller computational cost and has recently gained more research interes…

quant-ph2019

Quantum-assisted finite-element design optimization

Dyon van Vreumingen, Florian Neukart, David Von Dollen +4

Quantum annealing devices such as the ones produced by D-Wave systems are typically used for solving optimization and sampling tasks, and in both academia and industry the characte…