{"id":213834,"updated":"2025-01-19T17:00:14.901992+00:00","links":{},"created":"2025-01-19T01:14:40.710167+00:00","metadata":{"_oai":{"id":"oai:ipsj.ixsq.nii.ac.jp:00213834","sets":["1164:3616:10522:10751"]},"path":["10751"],"owner":"44499","recid":"213834","title":["最適輸送を用いた教師なしドメイン適応問題における輸送先クラスラベル推定に基づく識別部分空間学習"],"pubdate":{"attribute_name":"公開日","attribute_value":"2021-11-18"},"_buckets":{"deposit":"68095b05-431f-4562-bbf1-c7c40c527089"},"_deposit":{"id":"213834","pid":{"type":"depid","value":"213834","revision_id":0},"owners":[44499],"status":"published","created_by":44499},"item_title":"最適輸送を用いた教師なしドメイン適応問題における輸送先クラスラベル推定に基づく識別部分空間学習","author_link":["547636","547634","547635"],"item_titles":{"attribute_name":"タイトル","attribute_value_mlt":[{"subitem_title":"最適輸送を用いた教師なしドメイン適応問題における輸送先クラスラベル推定に基づく識別部分空間学習"},{"subitem_title":"Discriminative subspace learning with target class label estimation in unsupervised domain adaptation with optimal transport","subitem_title_language":"en"}]},"item_type_id":"4","publish_date":"2021-11-18","item_4_text_3":{"attribute_name":"著者所属","attribute_value_mlt":[{"subitem_text_value":"早稲田大学基幹理工学部情報通信学科"},{"subitem_text_value":"早稲田大学大学院基幹理工学研究科情報理工・通信専攻"},{"subitem_text_value":"早稲田大学基幹理工学部情報通信学科／早稲田大学大学院基幹理工学研究科情報理工・通信専攻"}]},"item_4_text_4":{"attribute_name":"著者所属(英)","attribute_value_mlt":[{"subitem_text_value":"Department of Communications and Computer Engineering, School of Fundamental Science and Engineering, Waseda University","subitem_text_language":"en"},{"subitem_text_value":"Department of Computer Science and Communications Engineering, Graduate School of Fundamental Science and Engineering, Waseda University","subitem_text_language":"en"},{"subitem_text_value":"Department of Communications and Computer Engineering, School of Fundamental Science and Engineering, Waseda University / Department of Computer Science and Communications Engineering, Graduate School of Fundamental Science and Engineering, Waseda University","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/213834/files/IPSJ-AVM21115014.pdf","label":"IPSJ-AVM21115014.pdf"},"date":[{"dateType":"Available","dateValue":"2023-11-18"}],"format":"application/pdf","billing":["billing_file"],"filename":"IPSJ-AVM21115014.pdf","filesize":[{"value":"753.9 kB"}],"mimetype":"application/pdf","priceinfo":[{"tax":["include_tax"],"price":"660","billingrole":"5"},{"tax":["include_tax"],"price":"330","billingrole":"6"},{"tax":["include_tax"],"price":"0","billingrole":"27"},{"tax":["include_tax"],"price":"0","billingrole":"44"}],"accessrole":"open_date","version_id":"26dcff7e-74fb-4928-9825-52d148117226","displaytype":"detail","licensetype":"license_note","license_note":"Copyright (c) 2021 by the Information Processing Society of Japan"}]},"item_4_creator_5":{"attribute_name":"著者名","attribute_type":"creator","attribute_value_mlt":[{"creatorNames":[{"creatorName":"北村, 優輝士"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"福永, 拓海"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"笠井, 裕之"}],"nameIdentifiers":[{}]}]},"item_4_source_id_9":{"attribute_name":"書誌レコードID","attribute_value_mlt":[{"subitem_source_identifier":"AN10438399","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":"2188-8582","subitem_source_identifier_type":"ISSN"}]},"item_4_description_7":{"attribute_name":"論文抄録","attribute_value_mlt":[{"subitem_description":"ドメイン適応問題は，ソース領域のラベルを利用することでラベル情報が不足しているターゲット領域の分類器の予測精度を向上する問題に利用される．この問題に対して，従来より，最適輸送問題を用いて分類性能を向上させる手法が提案されてきたが，近年，クラスラベル情報を考慮した計量学習により，部分空間へデータを射影した上で輸送を行う手法も提案されている．しかしながら，ターゲットデータについてはクラスラベルが存在しないことから部分空間の計量学習を行えないという問題がある．そこで本稿では，ターゲットデータについても計量学習を行って最適な部分空間を求めることを目的として，ターゲットデータのラベル推定と，推定ラベルに基づく計量学習による最適輸送を用いたドメイン適応手法を提案する．具体的には，ターゲットデータの確率的クラスラベル推定と推定ラベルを用いた確率的計量学習による部分空間学習により最適輸送ドメイン適応手法を提案する．","subitem_description_type":"Other"}]},"item_4_biblio_info_10":{"attribute_name":"書誌情報","attribute_value_mlt":[{"bibliographicPageEnd":"4","bibliographic_titles":[{"bibliographic_title":"研究報告オーディオビジュアル複合情報処理（AVM）"}],"bibliographicPageStart":"1","bibliographicIssueDates":{"bibliographicIssueDate":"2021-11-18","bibliographicIssueDateType":"Issued"},"bibliographicIssueNumber":"14","bibliographicVolumeNumber":"2021-AVM-115"}]},"relation_version_is_last":true,"weko_creator_id":"44499"}}