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06/30/2023
Comparing Algorithm Selection Approaches on Black-Box Optimization Problems
Performance complementarity of solvers available to tackle black-box opt...
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06/07/2023
Self-Adjusting Weighted Expected Improvement for Bayesian Optimization
Bayesian Optimization (BO) is a class of surrogate-based, sample-efficie...
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11/17/2022
Towards Automated Design of Bayesian Optimization via Exploratory Landscape Analysis
Bayesian optimization (BO) algorithms form a class of surrogate-based he...
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11/02/2022
PI is back! Switching Acquisition Functions in Bayesian Optimization
Bayesian Optimization (BO) is a powerful, sample-efficient technique to ...
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04/20/2022
Per-run Algorithm Selection with Warm-starting using Trajectory-based Features
Per-instance algorithm selection seeks to recommend, for a given problem...
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04/13/2022
Trajectory-based Algorithm Selection with Warm-starting
Landscape-aware algorithm selection approaches have so far mostly been r...
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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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04/19/2021
The Impact of Hyper-Parameter Tuning for Landscape-Aware Performance Regression and Algorithm Selection
Automated algorithm selection and configuration methods that build on ex...
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02/10/2021
Towards Feature-Based Performance Regression Using Trajectory Data
Black-box optimization is a very active area of research, with many new ...
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06/17/2020