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Jun Sakuma

Name: dblp XML data dump
Creator: Schloss Dagstuhl - Leibniz Center for Informatics
Published: 1993
License: https://creativecommons.org/publicdomain/zero/1.0/
Keywords: dblp, XML, computer science, scholarly publications, metadata

◀ ▶ joint publications with Atsuhiro Miyagi

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Publications

2023
[j18]
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  - journals/asc/MiyagiFSA23
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  - https://dblp.org/rec/journals/asc/MiyagiFSA23
Atsuhiro Miyagi, Kazuto Fukuchi, Jun Sakuma, Youhei Akimoto:
Adaptive scenario subset selection for worst-case optimization and its application to well placement optimization. Appl. Soft Comput. 133: 109842 (2023)
[j15]
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  - journals/telo/MiyagiMMFSA23
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Atsuhiro Miyagi, Yoshiki Miyauchi, Atsuo Maki, Kazuto Fukuchi, Jun Sakuma, Youhei Akimoto:
Covariance Matrix Adaptation Evolutionary Strategy with Worst-Case Ranking Approximation for Min-Max Optimization and Its Application to Berthing Control Tasks. ACM Trans. Evol. Learn. Optim. 3(2): 8:1-8:32 (2023)
[i34]
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  - journals/corr/abs-2303-16079
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Atsuhiro Miyagi, Yoshiki Miyauchi, Atsuo Maki, Kazuto Fukuchi, Jun Sakuma, Youhei Akimoto:
Covariance Matrix Adaptation Evolutionary Strategy with Worst-Case Ranking Approximation for Min-Max Optimization and its Application to Berthing Control Tasks. CoRR abs/2303.16079 (2023)
2022
[c83]
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  - conf/gecco/MiyagiFSA22
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Atsuhiro Miyagi, Kazuto Fukuchi, Jun Sakuma, Youhei Akimoto:
Black-box min-max continuous optimization using CMA-ES with worst-case ranking approximation. GECCO 2022: 823-831
[i28]
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  - journals/corr/abs-2204-02646
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Atsuhiro Miyagi, Kazuto Fukuchi, Jun Sakuma, Youhei Akimoto:
Black-Box Min-Max Continuous Optimization Using CMA-ES with Worst-case Ranking Approximation. CoRR abs/2204.02646 (2022)
[i24]
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  - journals/corr/abs-2211-16574
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Atsuhiro Miyagi, Kazuto Fukuchi, Jun Sakuma, Youhei Akimoto:
Adaptive Scenario Subset Selection for Worst-Case Optimization and its Application to Well Placement Optimization. CoRR abs/2211.16574 (2022)
2021
[c74]
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  - conf/gecco/MiyagiFSA21
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Atsuhiro Miyagi, Kazuto Fukuchi, Jun Sakuma, Youhei Akimoto:
Adaptive scenario subset selection for min-max black-box continuous optimization. GECCO 2021: 697-705

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