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Titlebook: Parallel Problem Solving from Nature – PPSN XVII; 17th International C Günter Rudolph,Anna V. Kononova,Tea Tu?ar Conference proceedings 202

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發(fā)表于 2025-3-23 09:49:24 | 只看該作者
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發(fā)表于 2025-3-23 20:35:38 | 只看該作者
Improving Nevergrad’s Algorithm Selection Wizard NGOpt Through Automated Algorithm Configurationhe problem and available computational resources, such as number and type of decision variables, maximal number of evaluations, possibility to parallelize evaluations, etc. State-of-the-art algorithm selection wizards are complex and difficult to improve. We propose in this work the use of automated
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發(fā)表于 2025-3-24 00:35:21 | 只看該作者
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發(fā)表于 2025-3-24 03:14:26 | 只看該作者
Per-run Algorithm Selection with?Warm-Starting Using Trajectory-Based Featuress that are expected to perform well for the particular setting. The selection is classically done offline, using openly available information about the problem instance or features that are extracted from the instance during a dedicated feature extraction step. This ignores valuable information that
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發(fā)表于 2025-3-24 06:50:29 | 只看該作者
A Systematic Approach to?Analyze the?Computational Cost of?Robustness in?Model-Assisted Robust Optimizationnal optimization problem into a robust counterpart, e.g.,?by taking an average of the function values over different perturbations to a specific input. Solving the robust counterpart instead of the original problem can significantly increase the associated computational cost, which is often overlook
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發(fā)表于 2025-3-24 14:08:26 | 只看該作者
Adaptive Function Value Warping for?Surrogate Model Assisted Evolutionary Optimizationms. Most surrogate modelling techniques in use with evolutionary algorithms today do not preserve the desirable invariance to order-preserving transformations of objective function values of the underlying algorithms. We propose adaptive function value warping as a tool aiming to reduce the sensitiv
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發(fā)表于 2025-3-24 16:18:08 | 只看該作者
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發(fā)表于 2025-3-24 20:40:41 | 只看該作者
Finding Knees in?Bayesian Multi-objective Optimizationber of objectives, extracting the Pareto front might not be easy nor cheap. On the other hand, the . is not always interested in the entire Pareto front, and might prefer a solution where there is a desirable trade-off between different objectives. An example of an attractive solution is the knee po
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發(fā)表于 2025-3-25 02:36:36 | 只看該作者
Risto Trajanov,Ana Nikolikj,Gjorgjina Cenikj,Fabien Teytaud,Mathurin Videau,Olivier Teytaud,Tome Eftimov,Manuel López-Ibá?ez,Carola Doerrer?nderte Kundenwünsche einstellen. Letztere wiederum sind einerseits von diesen Prozessen durch Ausdünnung der kostentr?chtigen Filialnetze betroffen, müssen ihr Geld per Online-Banking selbst verwalten und ein ganz neues Vertrauensverh?ltnis zu ihrem Finanzdienstleister aufbauen, der nun neben ihr
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