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06/08/2023
DynamoRep: Trajectory-Based Population Dynamics for Classification of Black-box Optimization Problems
The application of machine learning (ML) models to the analysis of optim...
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06/01/2023
Algorithm Instance Footprint: Separating Easily Solvable and Challenging Problem Instances
In black-box optimization, it is essential to understand why an algorith...
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05/31/2023
Assessing the Generalizability of a Performance Predictive Model
A key component of automated algorithm selection and configuration, whic...
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05/30/2023
Sensitivity Analysis of RF+clust for Leave-one-problem-out Performance Prediction
Leave-one-problem-out (LOPO) performance prediction requires machine lea...
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04/25/2022
SELECTOR: Selecting a Representative Benchmark Suite for Reproducible Statistical Comparison
Fair algorithm evaluation is conditioned on the existence of high-qualit...
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04/15/2022
The Importance of Landscape Features for Performance Prediction of Modular CMA-ES Variants
Selecting the most suitable algorithm and determining its hyperparameter...
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03/22/2022
Explainable Landscape Analysis in Automated Algorithm Performance Prediction
Predicting the performance of an optimization algorithm on a new problem...
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10/22/2021
Explainable Landscape-Aware Optimization Performance Prediction
Efficient solving of an unseen optimization problem is related to approp...
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04/27/2021
A Complementarity Analysis of the COCO Benchmark Problems and Artificially Generated Problems
When designing a benchmark problem set, it is important to create a set ...
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04/22/2021
Personalizing Performance Regression Models to Black-Box Optimization Problems
Accurately predicting the performance of different optimization algorith...
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09/30/2020