Conference
Benchmarking Large Scale Variants of CMA-ES and L-BFGS-B on the bbob-largescale Testbed
| العنوان: | Benchmarking Large Scale Variants of CMA-ES and L-BFGS-B on the bbob-largescale Testbed |
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| المؤلفون: | Varelas, Konstantinos |
| المساهمون: | Randomized Optimisation (RANDOPT), Centre de Mathématiques Appliquées de l'Ecole polytechnique (CMAP), Institut National de Recherche en Informatique et en Automatique (Inria)-École polytechnique (X), Institut Polytechnique de Paris (IP Paris)-Institut Polytechnique de Paris (IP Paris)-Centre National de la Recherche Scientifique (CNRS)-Institut National de Recherche en Informatique et en Automatique (Inria)-École polytechnique (X), Institut Polytechnique de Paris (IP Paris)-Institut Polytechnique de Paris (IP Paris)-Centre National de la Recherche Scientifique (CNRS)-Inria Saclay - Ile de France, Institut National de Recherche en Informatique et en Automatique (Inria), Thales LAS France |
| المصدر: | GECCO 2019 Companion - The Genetic and Evolutionary Computation Conference ; https://inria.hal.science/hal-02160106 ; GECCO 2019 Companion - The Genetic and Evolutionary Computation Conference, Jul 2019, Prague, Czech Republic. ⟨10.1145/3319619.3326893⟩ |
| بيانات النشر: | HAL CCSD |
| سنة النشر: | 2019 |
| مصطلحات موضوعية: | CMA-ES, Large scale variants, Continuous space search, Benchmarking, Black-box optimization, Large scale optimization, [INFO.INFO-NE]Computer Science [cs]/Neural and Evolutionary Computing [cs.NE], [MATH.MATH-OC]Mathematics [math]/Optimization and Control [math.OC] |
| جغرافية الموضوع: | Prague, Czech Republic |
| الوصف: | International audience ; In this paper we benchmark five variants of CMA-ES for optimization in large dimension on the novel large scale testbed of COCO under default or modified parameter settings. In particular, we compare the performance of the separable CMA-ES, of VD-CMA-ES and VkD-CMA-ES, of two implementations of the Limited Memory CMA-ES and of the Rank m Evolution Strategy, RmES. For VkD-CMA-ES we perform experiments with different complexity models of the search distribution and for RmES we study the impact of the number of evolution paths employed by the algorithm. The quasi-Newton L-BFGS-B algorithm is also benchmarked and we investigate the effect of choosing the maximum number of variable metric corrections for the Hessian approximation. As baseline comparison, we provide results of CMA-ES up to dimension 320. |
| نوع الوثيقة: | conference object |
| اللغة: | English |
| DOI: | 10.1145/3319619.3326893 |
| الاتاحة: | https://inria.hal.science/hal-02160106 https://inria.hal.science/hal-02160106v1/document https://inria.hal.science/hal-02160106v1/file/wksp213s2-file1.pdf https://doi.org/10.1145/3319619.3326893 |
| Rights: | info:eu-repo/semantics/OpenAccess |
| رقم الانضمام: | edsbas.3D94526F |
| قاعدة البيانات: | BASE |
| DOI: | 10.1145/3319619.3326893 |
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