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20132025
most citedOnline Selection of CMA-ES Variants

21 citations · 101 across the 36 of their papers we have counts for

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Showing 2020Show all

11 papers · 1 filter

cs.CV2020

Improving Model Accuracy for Imbalanced Image Classification Tasks by Adding a Final Batch Normalization Layer: An Empirical Study

Veysel Kocaman, Ofer M. Shir, Thomas Bäck

Some real-world domains, such as Agriculture and Healthcare, comprise early-stage disease indications whose recording constitutes a rare event, and yet, whose precise detection at…

cs.NE202014 cited

A Modular Hybridization of Particle Swarm Optimization and Differential Evolution

Rick Boks, Hao Wang, Thomas Bäck

In swarm intelligence, Particle Swarm Optimization (PSO) and Differential Evolution (DE) have been successfully applied in many optimization tasks, and a large number of variants,…

cs.LG2020

Discovering outstanding subgroup lists for numeric targets using MDL

Hugo M. Proença, Peter Grünwald, Thomas Bäck +1

The task of subgroup discovery (SD) is to find interpretable descriptions of subsets of a dataset that stand out with respect to a target attribute. To address the problem of minin…

cs.NE202016 cited

Towards Dynamic Algorithm Selection for Numerical Black-Box Optimization: Investigating BBOB as a Use Case

Diederick Vermetten, Hao Wang, Carola Doerr +1

One of the most challenging problems in evolutionary computation is to select from its family of diverse solvers one that performs well on a given problem. This algorithm selection…

cs.NE2020

Benchmarking a Genetic Algorithm with Configurable Crossover Probability

Furong Ye, Hao Wang, Carola Doerr +1

We investigate a family of Genetic Algorithms (GAs) which creates offspring either from mutation or by recombining two randomly chosen parents. By scaling the crossover pro…

cs.NE20201 cited

A Tailored NSGA-III Instantiation for Flexible Job Shop Scheduling

Yali Wang, Bas van Stein, Michael T. M. Emmerich +1

A customized multi-objective evolutionary algorithm (MOEA) is proposed for the multi-objective flexible job shop scheduling problem (FJSP). It uses smart initialization approaches…