Search Results - Automated algorithm design
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Authors: et al.
Source: Complex & Intelligent Systems, Vol 10, Iss 6, Pp 8233-8247 (2024)
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Authors: et al.
Source: 2024 IEEE 17th International Conference on Signal Processing (ICSP). :284-289
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Authors: et al.
Subject Terms: Machine Learning, FOS: Computer and information sciences, Artificial Intelligence (cs.AI), Artificial Intelligence, Machine Learning (cs.LG)
Access URL: http://arxiv.org/abs/2507.10614
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Authors: et al.
Subject Terms: Optimization and Control (math.OC), Optimization and Control, FOS: Mathematics, FOS: Electrical engineering, electronic engineering, information engineering, Systems and Control (eess.SY), Dynamical Systems (math.DS), Dynamical Systems, Systems and Control
Access URL: http://arxiv.org/abs/2509.20746
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Authors:
Source: Evolutionary computation [Evol Comput] 2025 Oct 31, pp. 1-27. Date of Electronic Publication: 2025 Oct 31.
Publication Type: Journal Article
Journal Info: Publisher: MIT Press Country of Publication: United States NLM ID: 9513581 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 1530-9304 (Electronic) Linking ISSN: 10636560 NLM ISO Abbreviation: Evol Comput Subsets: MEDLINE
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Authors: et al.
Source: International journal of computer assisted radiology and surgery [Int J Comput Assist Radiol Surg] 2024 Nov; Vol. 19 (11), pp. 2279-2285. Date of Electronic Publication: 2024 Jun 06.
Publication Type: Journal Article
Journal Info: Publisher: Springer Country of Publication: Germany NLM ID: 101499225 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 1861-6429 (Electronic) Linking ISSN: 18616410 NLM ISO Abbreviation: Int J Comput Assist Radiol Surg Subsets: MEDLINE
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Authors: et al.
Contributors: et al.
Subject Terms: hyper-parameter tuning, automated algorithm design, parameter control, ddc:004, black-box optimization, heuristic optimization
File Description: application/pdf
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Authors: et al.
Index Terms: automated algorithm design, hyper-parameter tuning, parameter control, heuristic optimization, black-box optimization, Article, Text, doc-type:ResearchArticle, publishedVersion
URL:
https://drops.dagstuhl.de/entities/document/10.4230/DagRep.13.8.46
Is Part Of Dagstuhl Reports, Volume 13, Issue 8 (2024) -
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Authors: et al.
Source: International Journal of Production Research. Oct2025, Vol. 63 Issue 20, p7570-7590. 21p.
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Contributors:
Source: Proceedings of the Genetic and Evolutionary Computation Conference Companion. :1365-1374
Subject Terms: FOS: Computer and information sciences, [INFO.INFO-NE] Computer Science [cs]/Neural and Evolutionary Computing [cs.NE], 0202 electrical engineering, electronic engineering, information engineering, Computer Science - Neural and Evolutionary Computing, Neural and Evolutionary Computing (cs.NE), 02 engineering and technology
File Description: application/pdf
Access URL: http://arxiv.org/pdf/2102.06435
http://arxiv.org/abs/2102.06435
http://ui.adsabs.harvard.edu/abs/2021arXiv210206435A/abstract
http://export.arxiv.org/pdf/2102.06435
http://arxiv.org/pdf/2102.06435.pdf
https://arxiv.org/abs/2102.06435
https://dblp.uni-trier.de/db/journals/corr/corr2102.html#abs-2102-06435
https://arxiv.org/abs/2102.06435
https://dl.acm.org/doi/pdf/10.1145/3449726.3463155
https://arxiv.org/pdf/2102.06435
https://hal.sorbonne-universite.fr/hal-03233932v1/document
https://doi.org/10.1145/3449726.3463155
https://hal.sorbonne-universite.fr/hal-03233932v1 -
15
Authors: et al.
Source: Diabetes technology & therapeutics [Diabetes Technol Ther] 2024 Oct; Vol. 26 (10), pp. 783-784. Date of Electronic Publication: 2024 Apr 25.
Publication Type: Letter
Journal Info: Publisher: Mary Ann Liebert, Inc Country of Publication: United States NLM ID: 100889084 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 1557-8593 (Electronic) Linking ISSN: 15209156 NLM ISO Abbreviation: Diabetes Technol Ther Subsets: MEDLINE
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Authors: et al.
Source: IEEE Transactions on Evolutionary Computation. :1-1
Subject Terms: FOS: Computer and information sciences, Computer Science - Machine Learning, Computer Science - Neural and Evolutionary Computing, Neural and Evolutionary Computing (cs.NE), Machine Learning (cs.LG)
Access URL: http://arxiv.org/abs/2411.00625
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Authors:
Source: Diabetes technology & therapeutics [Diabetes Technol Ther] 2024 Oct; Vol. 26 (10), pp. 785-786. Date of Electronic Publication: 2024 Apr 05.
Publication Type: Letter
Journal Info: Publisher: Mary Ann Liebert, Inc Country of Publication: United States NLM ID: 100889084 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 1557-8593 (Electronic) Linking ISSN: 15209156 NLM ISO Abbreviation: Diabetes Technol Ther Subsets: MEDLINE
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Authors: et al.
Source: Journal of the ACM. 71:1-58
Subject Terms: 0301 basic medicine, data-driven algorithm design, 0303 health sciences, 03 medical and health sciences, machine learning, computational biology, General topics in the theory of algorithms, Learning and adaptive systems in artificial intelligence, automated algorithm design, automated algorithm configuration
File Description: application/xml
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Authors: et al.
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Authors: et al.
Contributors: et al.
Source: Proceedings of the Genetic and Evolutionary Computation Conference Companion. :1522-1530
Subject Terms: [INFO.INFO-AI] Computer Science [cs]/Artificial Intelligence [cs.AI], FOS: Computer and information sciences, 0211 other engineering and technologies, Computer Science - Neural and Evolutionary Computing, Metaheuristics, 02 engineering and technology, [INFO.INFO-MS] Computer Science [cs]/Mathematical Software [cs.MS], Software Framework, Automated Algorithm Design, 0202 electrical engineering, electronic engineering, information engineering, Computer Science - Mathematical Software, Neural and Evolutionary Computing (cs.NE), Evolutionary Computation, Mathematical Software (cs.MS)
File Description: application/pdf
Access URL: http://arxiv.org/pdf/2105.00420
http://arxiv.org/abs/2105.00420
https://dl.acm.org/doi/pdf/10.1145/3449726.3463276
https://dblp.uni-trier.de/db/journals/corr/corr2105.html#abs-2105-00420
https://arxiv.org/abs/2105.00420
https://arxiv.org/pdf/2105.00420
http://ui.adsabs.harvard.edu/abs/2021arXiv210500420D/abstract
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