{"links":{},"id":211741,"metadata":{"_oai":{"id":"oai:ipsj.ixsq.nii.ac.jp:00211741","sets":["1164:2735:10526:10613"]},"path":["10613"],"owner":"44499","recid":"211741","title":["分布的ロバストな機会制約付き最適化問題に対する能動学習"],"pubdate":{"attribute_name":"公開日","attribute_value":"2021-06-21"},"_buckets":{"deposit":"bb49b620-dd73-45f8-8393-25dfded96b47"},"_deposit":{"id":"211741","pid":{"type":"depid","value":"211741","revision_id":0},"owners":[44499],"status":"published","created_by":44499},"item_title":"分布的ロバストな機会制約付き最適化問題に対する能動学習","author_link":["538483","538485","538488","538487","538489","538484","538486","538490"],"item_titles":{"attribute_name":"タイトル","attribute_value_mlt":[{"subitem_title":"分布的ロバストな機会制約付き最適化問題に対する能動学習"},{"subitem_title":"Active learning for distributionally robust chance-constrained optimization","subitem_title_language":"en"}]},"item_keyword":{"attribute_name":"キーワード","attribute_value_mlt":[{"subitem_subject":"自動運転・学習理論","subitem_subject_scheme":"Other"}]},"item_type_id":"4","publish_date":"2021-06-21","item_4_text_3":{"attribute_name":"著者所属","attribute_value_mlt":[{"subitem_text_value":"名古屋工業大学"},{"subitem_text_value":"名古屋工業大学"},{"subitem_text_value":"名古屋工業大学::名古屋工業大学／理化学研究所"}]},"item_4_text_4":{"attribute_name":"著者所属(英)","attribute_value_mlt":[{"subitem_text_value":"Nagoya Institute of Technology","subitem_text_language":"en"},{"subitem_text_value":"Nagoya Institute of Technology","subitem_text_language":"en"},{"subitem_text_value":"Nagoya Institute of Technology","subitem_text_language":"en"},{"subitem_text_value":"Nagoya Institute of Technology / RIKEN Center for Advanced Intelligence Project","subitem_text_language":"en"}]},"item_language":{"attribute_name":"言語","attribute_value_mlt":[{"subitem_language":"jpn"}]},"item_publisher":{"attribute_name":"出版者","attribute_value_mlt":[{"subitem_publisher":"情報処理学会","subitem_publisher_language":"ja"}]},"publish_status":"0","weko_shared_id":-1,"item_file_price":{"attribute_name":"Billing file","attribute_type":"file","attribute_value_mlt":[{"url":{"url":"https://ipsj.ixsq.nii.ac.jp/record/211741/files/IPSJ-MPS21133007.pdf","label":"IPSJ-MPS21133007.pdf"},"format":"application/pdf","billing":["billing_file"],"filename":"IPSJ-MPS21133007.pdf","filesize":[{"value":"1.7 MB"}],"mimetype":"application/pdf","priceinfo":[{"tax":["include_tax"],"price":"0","billingrole":"17"},{"tax":["include_tax"],"price":"0","billingrole":"44"}],"accessrole":"open_login","version_id":"b22325c1-d481-447f-9045-918d80691555","displaytype":"detail","licensetype":"license_note","license_note":"Copyright (c) 2021 by the Institute of Electronics, Information and Communication Engineers This SIG report is only available to those in membership of the SIG."}]},"item_4_creator_5":{"attribute_name":"著者名","attribute_type":"creator","attribute_value_mlt":[{"creatorNames":[{"creatorName":"稲津, 佑"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"竹野, 思温"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"烏山, 昌幸"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"竹内, 一郎"}],"nameIdentifiers":[{}]}]},"item_4_creator_6":{"attribute_name":"著者名(英)","attribute_type":"creator","attribute_value_mlt":[{"creatorNames":[{"creatorName":"Yu, Inatsu","creatorNameLang":"en"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"Shion, Takeno","creatorNameLang":"en"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"Masayuki, Karasuyama","creatorNameLang":"en"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"Ichiro, Takeuchi","creatorNameLang":"en"}],"nameIdentifiers":[{}]}]},"item_4_source_id_9":{"attribute_name":"書誌レコードID","attribute_value_mlt":[{"subitem_source_identifier":"AN10505667","subitem_source_identifier_type":"NCID"}]},"item_4_textarea_12":{"attribute_name":"Notice","attribute_value_mlt":[{"subitem_textarea_value":"SIG Technical Reports are nonrefereed and hence may later appear in any journals, conferences, symposia, etc."}]},"item_resource_type":{"attribute_name":"資源タイプ","attribute_value_mlt":[{"resourceuri":"http://purl.org/coar/resource_type/c_18gh","resourcetype":"technical report"}]},"item_4_source_id_11":{"attribute_name":"ISSN","attribute_value_mlt":[{"subitem_source_identifier":"2188-8833","subitem_source_identifier_type":"ISSN"}]},"item_4_description_7":{"attribute_name":"論文抄録","attribute_value_mlt":[{"subitem_description":"ブラックボックス関数の入力の一部が確率変数で与えられるもとでの制約付き最適化問題のひとつに，機会制約付き最適化問題 (Chance-constrained optimization，CCO) がある．この問題は確率変数の分布が既知でなければならず，分布が未知の場合は分布の誤特定の影響を考慮する必要がある．本研究では，確率変数の候補分布族の中での最悪ケースにおける CCO を考えることにより，分布の誤特定に関してロバストな CCO を考え，この最適化問題を効率的に解くための能動学習法を提案する．","subitem_description_type":"Other"}]},"item_4_description_8":{"attribute_name":"論文抄録(英)","attribute_value_mlt":[{"subitem_description":"Chance-constrained optimization (CCO) is one of the constrained optimization problems where some of the inputs to a black-box function are given by random variables. In this problem, the distribution of the random variables must be known, and if the distribution is unknown, the effect of misspecification of the distribution must be taken into account. In this study, we consider CCO in the worst case among the candidate family of distributions for random variables, and propose an active learning method to solve this optimization problem efficiently.","subitem_description_type":"Other"}]},"item_4_biblio_info_10":{"attribute_name":"書誌情報","attribute_value_mlt":[{"bibliographicPageEnd":"7","bibliographic_titles":[{"bibliographic_title":"研究報告数理モデル化と問題解決（MPS）"}],"bibliographicPageStart":"1","bibliographicIssueDates":{"bibliographicIssueDate":"2021-06-21","bibliographicIssueDateType":"Issued"},"bibliographicIssueNumber":"7","bibliographicVolumeNumber":"2021-MPS-133"}]},"relation_version_is_last":true,"weko_creator_id":"44499"},"created":"2025-01-19T01:12:52.721549+00:00","updated":"2025-01-19T17:41:51.406615+00:00"}