{"links":{},"metadata":{"_oai":{"id":"oai:ipsj.ixsq.nii.ac.jp:00241183","sets":["1164:4619:11539:11858"]},"path":["11858"],"owner":"44499","recid":"241183","title":["グループ間性能均衡化：Boostingに基づくアルゴリズムと理論保証"],"pubdate":{"attribute_name":"公開日","attribute_value":"2024-11-22"},"_buckets":{"deposit":"d63d3e8e-4eff-4c22-81b4-23d11508678b"},"_deposit":{"id":"241183","pid":{"type":"depid","value":"241183","revision_id":0},"owners":[44499],"status":"published","created_by":44499},"item_title":"グループ間性能均衡化：Boostingに基づくアルゴリズムと理論保証","author_link":["663579","663580","663581","663578"],"item_titles":{"attribute_name":"タイトル","attribute_value_mlt":[{"subitem_title":"グループ間性能均衡化：Boostingに基づくアルゴリズムと理論保証"}]},"item_type_id":"4","publish_date":"2024-11-22","item_4_text_3":{"attribute_name":"著者所属","attribute_value_mlt":[{"subitem_text_value":"九州大学大学院システム情報科学府"},{"subitem_text_value":"九州大学大学院システム情報科学府"},{"subitem_text_value":"九州大学大学院システム情報科学府"},{"subitem_text_value":"九州大学大学院システム情報科学府／理化学研究所"}]},"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/241183/files/IPSJ-CVIM24239038.pdf","label":"IPSJ-CVIM24239038.pdf"},"format":"application/pdf","billing":["billing_file"],"filename":"IPSJ-CVIM24239038.pdf","filesize":[{"value":"1.3 MB"}],"mimetype":"application/pdf","priceinfo":[{"tax":["include_tax"],"price":"0","billingrole":"20"},{"tax":["include_tax"],"price":"0","billingrole":"44"}],"accessrole":"open_login","version_id":"f0257df7-0182-4ee7-ad89-108a963c2fb2","displaytype":"detail","licensetype":"license_note","license_note":"Copyright (c) 2024 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":"斉藤, 優也"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"松尾, 信之介"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"内田, 誠一"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"末廣, 大貴"}],"nameIdentifiers":[{}]}]},"item_4_source_id_9":{"attribute_name":"書誌レコードID","attribute_value_mlt":[{"subitem_source_identifier":"AA11131797","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":"2188-8701","subitem_source_identifier_type":"ISSN"}]},"item_4_description_7":{"attribute_name":"論文抄録","attribute_value_mlt":[{"subitem_description":"クラス分類学習では，特定のグループの予測性能が悪化してしまう問題がある．特に，性別や国籍などグループ間で予測性能に不均衡が起こることは実用上で重大な問題となる．本稿では，最も誤差が大きいグループの誤差（最悪グループ誤差）を抑えることで，グループ間の予測性能の均衡化に取り組む．過学習を考慮した最悪グループ誤差抑制の問題定式化および，Boosting の枠組みを用いた学習アルゴリズムを提案する．また，最悪グループ訓練誤差および汎化誤差に関する理論保証を示す．人工データと実画像データを用いた実験を行い，提案法の有効性を検証する．","subitem_description_type":"Other"}]},"item_4_biblio_info_10":{"attribute_name":"書誌情報","attribute_value_mlt":[{"bibliographicPageEnd":"5","bibliographic_titles":[{"bibliographic_title":"研究報告コンピュータビジョンとイメージメディア（CVIM）"}],"bibliographicPageStart":"1","bibliographicIssueDates":{"bibliographicIssueDate":"2024-11-22","bibliographicIssueDateType":"Issued"},"bibliographicIssueNumber":"38","bibliographicVolumeNumber":"2024-CVIM-239"}]},"relation_version_is_last":true,"weko_creator_id":"44499"},"created":"2025-01-19T01:45:48.459826+00:00","updated":"2025-01-19T07:43:07.012058+00:00","id":241183}