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Titlebook: Optimization and Learning; 5th International Co Bernabé Dorronsoro,Mario Pavone,El-Ghazali Talbi Conference proceedings 2022 The Editor(s)

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發(fā)表于 2025-3-21 17:46:15 | 只看該作者 |倒序?yàn)g覽 |閱讀模式
書目名稱Optimization and Learning
副標(biāo)題5th International Co
編輯Bernabé Dorronsoro,Mario Pavone,El-Ghazali Talbi
視頻videohttp://file.papertrans.cn/704/703218/703218.mp4
叢書名稱Communications in Computer and Information Science
圖書封面Titlebook: Optimization and Learning; 5th International Co Bernabé Dorronsoro,Mario Pavone,El-Ghazali Talbi Conference proceedings 2022 The Editor(s)
描述This book constitutes the refereed proceedings of the 5th International Conference on Optimization and Learning, OLA 2022, which took place in Syracuse, Sicilia, Italy, in July 2022.?.The 19 full papers presented in this volume were carefully reviewed and selected from 52 submissions. The papers are organized in the following topical sections: Optimization and Learning; Novel Optimization Techniques; Logistics; and Applications..
出版日期Conference proceedings 2022
關(guān)鍵詞artificial intelligence; computer programming; correlation analysis; distributed computer systems; distr
版次1
doihttps://doi.org/10.1007/978-3-031-22039-5
isbn_softcover978-3-031-22038-8
isbn_ebook978-3-031-22039-5Series ISSN 1865-0929 Series E-ISSN 1865-0937
issn_series 1865-0929
copyrightThe Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerl
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書目名稱Optimization and Learning影響因子(影響力)




書目名稱Optimization and Learning影響因子(影響力)學(xué)科排名




書目名稱Optimization and Learning網(wǎng)絡(luò)公開(kāi)度




書目名稱Optimization and Learning網(wǎng)絡(luò)公開(kāi)度學(xué)科排名




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Multi-objective Hyperparameter Optimization with?Performance Uncertaintyeterogeneous noise. Experimental results on three analytical test functions and three ML problems show the improvement in the hypervolume obtained, when compared with HPO using stand-alone multi-objective TPE and GPR.
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Tuning ForestDisc Hyperparameters: A Sensitivity Analysis based on moment matching optimization. Previous works showed that ForestDisc enables an excellent performance compared to 22 popular discretizers. This work analyzes ForestDisc performance sensitivity to its tunning parameters and provides some guidelines for users when using the ForestDisc package.
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Neural Order-First Split-Second Algorithm for?the?Capacitated Vehicle Routing Probleml and a dynamic programming shortest path algorithm (Split). Our results, based on intensive experiments with several neural network model architectures, show that such a two-step hybridization enables learning of implicit algorithms (i.e. policies) producing competitive solutions for the CVRP.
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1865-0929 papers are organized in the following topical sections: Optimization and Learning; Novel Optimization Techniques; Logistics; and Applications..978-3-031-22038-8978-3-031-22039-5Series ISSN 1865-0929 Series E-ISSN 1865-0937
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