{"id":217155,"metadata":{"_oai":{"id":"oai:ipsj.ixsq.nii.ac.jp:00217155","sets":["1164:2036:10820:10893"]},"path":["10893"],"owner":"44499","recid":"217155","title":["分岐命令の選択的近似による決定木アンサンブルの高速化"],"pubdate":{"attribute_name":"公開日","attribute_value":"2022-03-03"},"_buckets":{"deposit":"f0355f0f-d1ec-4ddc-8425-c23e65719169"},"_deposit":{"id":"217155","pid":{"type":"depid","value":"217155","revision_id":0},"owners":[44499],"status":"published","created_by":44499},"item_title":"分岐命令の選択的近似による決定木アンサンブルの高速化","author_link":["562046","562047"],"item_titles":{"attribute_name":"タイトル","attribute_value_mlt":[{"subitem_title":"分岐命令の選択的近似による決定木アンサンブルの高速化"}]},"item_keyword":{"attribute_name":"キーワード","attribute_value_mlt":[{"subitem_subject":"プロセッサ・アーキテクチャ","subitem_subject_scheme":"Other"}]},"item_type_id":"4","publish_date":"2022-03-03","item_4_text_3":{"attribute_name":"著者所属","attribute_value_mlt":[{"subitem_text_value":"東京大学"},{"subitem_text_value":"東京大学"}]},"item_4_text_4":{"attribute_name":"著者所属(英)","attribute_value_mlt":[{"subitem_text_value":"The University of Tokyo","subitem_text_language":"en"},{"subitem_text_value":"The University of Tokyo","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/217155/files/IPSJ-SLDM22198001.pdf","label":"IPSJ-SLDM22198001.pdf"},"date":[{"dateType":"Available","dateValue":"2024-03-03"}],"format":"application/pdf","billing":["billing_file"],"filename":"IPSJ-SLDM22198001.pdf","filesize":[{"value":"743.4 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":"10"},{"tax":["include_tax"],"price":"0","billingrole":"44"}],"accessrole":"open_date","version_id":"51fa4d65-6f81-4116-98ac-3501b2d685ea","displaytype":"detail","licensetype":"license_note","license_note":"Copyright (c) 2022 by the Information Processing Society of Japan"}]},"item_4_creator_5":{"attribute_name":"著者名","attribute_type":"creator","attribute_value_mlt":[{"creatorNames":[{"creatorName":"釡堀, 恵輔"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"高前田, 伸也"}],"nameIdentifiers":[{}]}]},"item_4_source_id_9":{"attribute_name":"書誌レコードID","attribute_value_mlt":[{"subitem_source_identifier":"AA11451459","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":"2188-8639","subitem_source_identifier_type":"ISSN"}]},"item_4_description_7":{"attribute_name":"論文抄録","attribute_value_mlt":[{"subitem_description":"軽量な組込みプロセッサで効率的に機械学習処理を行うためには，エネルギーやリソース使用量を節約できる高速化機構が望まれている．本論文では，機械学習モデルの精度といったサービスの品質を確保しつつ，プログラマによるアノテーションに基づき，軽量なプロセッサ上で決定木アンサンブルなどの機械学習アプリケーションの性能を改善する近似計算手法を提案する．本手法は，決定木中の重要度などに基づき選択された分岐命令について，分岐予測ミスの際にロールバックを行わずに，誤った分岐パスをそのまま継続実行することで，性能向上を目指す．提案手法はエッジデバイス上の機械学習アプリケーションを高速化するための有望なアプローチとなると考えられる．","subitem_description_type":"Other"}]},"item_4_biblio_info_10":{"attribute_name":"書誌情報","attribute_value_mlt":[{"bibliographicPageEnd":"4","bibliographic_titles":[{"bibliographic_title":"研究報告システムとLSIの設計技術（SLDM）"}],"bibliographicPageStart":"1","bibliographicIssueDates":{"bibliographicIssueDate":"2022-03-03","bibliographicIssueDateType":"Issued"},"bibliographicIssueNumber":"1","bibliographicVolumeNumber":"2022-SLDM-198"}]},"relation_version_is_last":true,"weko_creator_id":"44499"},"updated":"2025-01-19T15:36:06.867825+00:00","created":"2025-01-19T01:17:39.574026+00:00","links":{}}