{"metadata":{"_oai":{"id":"oai:ipsj.ixsq.nii.ac.jp:00240514","sets":["1164:2036:11466:11785"]},"path":["11785"],"owner":"44499","recid":"240514","title":["説明可能なAIを用いた精度を考慮した回路近似手法"],"pubdate":{"attribute_name":"公開日","attribute_value":"2024-11-05"},"_buckets":{"deposit":"5d34db73-a3b8-4cbc-a57c-c2ed16ab6fbc"},"_deposit":{"id":"240514","pid":{"type":"depid","value":"240514","revision_id":0},"owners":[44499],"status":"published","created_by":44499},"item_title":"説明可能なAIを用いた精度を考慮した回路近似手法","author_link":["659948"],"item_titles":{"attribute_name":"タイトル","attribute_value_mlt":[{"subitem_title":"説明可能なAIを用いた精度を考慮した回路近似手法"}]},"item_type_id":"4","publish_date":"2024-11-05","item_4_text_3":{"attribute_name":"著者所属","attribute_value_mlt":[{"subitem_text_value":"会津大学コンピュータ理工学部"}]},"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/240514/files/IPSJ-SLDM24207032.pdf","label":"IPSJ-SLDM24207032.pdf"},"format":"application/pdf","billing":["billing_file"],"filename":"IPSJ-SLDM24207032.pdf","filesize":[{"value":"1.3 MB"}],"mimetype":"application/pdf","priceinfo":[{"tax":["include_tax"],"price":"0","billingrole":"10"},{"tax":["include_tax"],"price":"0","billingrole":"44"}],"accessrole":"open_login","version_id":"8aa55ce2-ce88-4767-b9f4-26e2b842ec46","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":"小平, 行秀"}],"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":"近年，画像処理や機械学習などの計算量の多いアプリケーションに対して，精度に重大な影響を及ぼさない範囲で誤差を含むことを許容し，計算の高速化や低電力化を図る近似計算 (Approximate Computing) が注目を集めている．出力に対して影響の小さい部分を特定し，その部分に対して近似を適用すると，近似誤差が小さくなると考えられるが，回路全体からそのような部分を特定することは難しい．そこで本稿では，説明可能な AI を用いて，回路の各信号に対して，出力に対する影響度を算出する手法を提案する．説明可能な AI として LIME と SHAP を比較し，回路の近似に対しては SHAP が有効であることを示す．さらに，SHAP を元にした提案手法を小規模な回路に適用し，回路の近似に対して提案手法が有効であることを確認する．","subitem_description_type":"Other"}]},"item_4_biblio_info_10":{"attribute_name":"書誌情報","attribute_value_mlt":[{"bibliographicPageEnd":"6","bibliographic_titles":[{"bibliographic_title":"研究報告システムとLSIの設計技術（SLDM）"}],"bibliographicPageStart":"1","bibliographicIssueDates":{"bibliographicIssueDate":"2024-11-05","bibliographicIssueDateType":"Issued"},"bibliographicIssueNumber":"32","bibliographicVolumeNumber":"2024-SLDM-207"}]},"relation_version_is_last":true,"weko_creator_id":"44499"},"id":240514,"updated":"2025-01-19T07:57:20.793904+00:00","links":{},"created":"2025-01-19T01:44:44.820748+00:00"}