Showing 1–20 of 137 results
/ Date/ Name
Jun 19, 2020Hybridizing the 1/5-th Success Rule with Q-Learning for Controlling the Mutation Rate of an Evolutionary AlgorithmApr 22, 2021Personalizing Performance Regression Models to Black-Box Optimization ProblemsFeb 12, 2021Towards Large Scale Automated Algorithm Design by Integrating Modular Benchmarking FrameworksFeb 1, 2019Fast Re-Optimization via Structural DiversityJan 24, 2023Using Knowledge Graphs for Performance Prediction of Modular Optimization AlgorithmsJun 1, 2023Algorithm Instance Footprint: Separating Easily Solvable and Challenging Problem InstancesFeb 15, 2013Rumor Spreading in Random Evolving GraphsJun 19, 2015Solving Problems with Unknown Solution Length at (Almost) No Extra CostFeb 15, 2018Discrepancy-based Evolutionary Diversity OptimizationApr 16, 2018Theory of Parameter Control for Discrete Black-Box Optimization: Provable Performance Gains Through Dynamic Parameter ChoicesNov 21, 2022Explainable Model-specific Algorithm Selection for Multi-Label ClassificationNov 4, 2025Optimizing Kernel Discrepancies via Subset SelectionFeb 23, 2023Using Automated Algorithm Configuration for Parameter ControlNov 21, 2022OPTION: OPTImization Algorithm Benchmarking ONtologySep 29, 2023Optimizing with Low Budgets: a Comparison on the Black-box Optimization Benchmarking Suite and OpenAI GymApr 24, 2024Empirical Analysis of the Dynamic Binary Value Problem with IOHprofilerApr 11, 2024Impact of Training Instance Selection on Automated Algorithm Selection Models for Numerical Black-box OptimizationDec 20, 2018The Query Complexity of a Permutation-Based Variant of MastermindApr 27, 2020MATE: A Model-based Algorithm Tuning EngineApr 8, 2016The (1+1) Elitist Black-Box Complexity of LeadingOnes