{"links":{},"id":235054,"metadata":{"_oai":{"id":"oai:ipsj.ixsq.nii.ac.jp:00235054","sets":["1164:10193:11470:11670"]},"path":["11670"],"owner":"44499","recid":"235054","title":["連続量による量子アニーリングを用いた線形回帰"],"pubdate":{"attribute_name":"公開日","attribute_value":"2024-06-20"},"_buckets":{"deposit":"3289a953-a280-46aa-8e89-42e244a5dddb"},"_deposit":{"id":"235054","pid":{"type":"depid","value":"235054","revision_id":0},"owners":[44499],"status":"published","created_by":44499},"item_title":"連続量による量子アニーリングを用いた線形回帰","author_link":["641737","641736","641735","641738"],"item_titles":{"attribute_name":"タイトル","attribute_value_mlt":[{"subitem_title":"連続量による量子アニーリングを用いた線形回帰"}]},"item_type_id":"4","publish_date":"2024-06-20","item_4_text_3":{"attribute_name":"著者所属","attribute_value_mlt":[{"subitem_text_value":"Department of Electrical, Electronic, and Communication Engineering, Chuo University"},{"subitem_text_value":"Global Research and Development Center for Business by Quantum-AI Technology (G-QuAT), AIST"},{"subitem_text_value":"Global Research and Development Center for Business by Quantum-AI Technology (G-QuAT), AIST"},{"subitem_text_value":"Global Research and Development Center for Business by Quantum-AI Technology (G-QuAT), AIST／Department of Electrical, Electronic, and Communication Engineering, Chuo University"}]},"item_4_text_4":{"attribute_name":"著者所属(英)","attribute_value_mlt":[{"subitem_text_value":"Department of Electrical, Electronic, and Communication Engineering, Chuo University","subitem_text_language":"en"},{"subitem_text_value":"Global Research and Development Center for Business by Quantum-AI Technology (G-QuAT), AIST","subitem_text_language":"en"},{"subitem_text_value":"Global Research and Development Center for Business by Quantum-AI Technology (G-QuAT), AIST","subitem_text_language":"en"},{"subitem_text_value":"Global Research and Development Center for Business by Quantum-AI Technology (G-QuAT), AIST / Department of Electrical, Electronic, and Communication Engineering, Chuo 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/235054/files/IPSJ-QS24012007.pdf","label":"IPSJ-QS24012007.pdf"},"date":[{"dateType":"Available","dateValue":"2026-06-20"}],"format":"application/pdf","billing":["billing_file"],"filename":"IPSJ-QS24012007.pdf","filesize":[{"value":"2.3 MB"}],"mimetype":"application/pdf","priceinfo":[{"tax":["include_tax"],"price":"660","billingrole":"5"},{"tax":["include_tax"],"price":"330","billingrole":"6"},{"tax":["include_tax"],"price":"0","billingrole":"53"},{"tax":["include_tax"],"price":"0","billingrole":"44"}],"accessrole":"open_date","version_id":"fa5dbd86-54a7-4157-976b-f693904defee","displaytype":"detail","licensetype":"license_note","license_note":"Copyright (c) 2024 by the Information Processing Society of Japan"}]},"item_4_creator_5":{"attribute_name":"著者名","attribute_type":"creator","attribute_value_mlt":[{"creatorNames":[{"creatorName":"高良, 明日香"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"井元, 隆史"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"浦, 優輝"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"松崎, 雄一郎"}],"nameIdentifiers":[{}]}]},"item_4_source_id_9":{"attribute_name":"書誌レコードID","attribute_value_mlt":[{"subitem_source_identifier":"AA12894105","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":"2435-6492","subitem_source_identifier_type":"ISSN"}]},"item_4_description_7":{"attribute_name":"論文抄録","attribute_value_mlt":[{"subitem_description":"線形回帰は既知のデータ値を利用して，未知のデータを予測する教師あり学習の一つであり，データ分析手法の一種である．近年，量子アニーリングを用いた線形回帰の学習が提案・実証された．従来手法では，変数を二進数で展開することで離散的な値に近似したうえで，量子アニーリングで線形回帰を行っていた．しかし，このアプローチでは精度を向上させるためには，量子ビット数を増やさなければならないという難点が存在した．そこで我々は，連続量による量子アニーリングを用いた線形回帰を提案する．ボゾン系を用いることで，連続的な変数を直接扱って量子アニーリングを実行して線形回帰を実行できる．断熱条件を満たしていれば，量子デバイスの数を増やすことなく精度を担保できる点に大きな特徴がある．","subitem_description_type":"Other"}]},"item_4_biblio_info_10":{"attribute_name":"書誌情報","attribute_value_mlt":[{"bibliographicPageEnd":"10","bibliographic_titles":[{"bibliographic_title":"研究報告量子ソフトウェア（QS）"}],"bibliographicPageStart":"1","bibliographicIssueDates":{"bibliographicIssueDate":"2024-06-20","bibliographicIssueDateType":"Issued"},"bibliographicIssueNumber":"7","bibliographicVolumeNumber":"2024-QS-12"}]},"relation_version_is_last":true,"weko_creator_id":"44499"},"created":"2025-01-19T01:37:02.501969+00:00","updated":"2025-01-19T09:37:24.601326+00:00"}