{"updated":"2025-01-19T18:40:25.962802+00:00","metadata":{"_oai":{"id":"oai:ipsj.ixsq.nii.ac.jp:00208942","sets":["1164:2836:10118:10461"]},"path":["10461"],"owner":"44499","recid":"208942","title":["セキュアマルチパーティ計算によるエッジシステム上のBP学習法の提案"],"pubdate":{"attribute_name":"公開日","attribute_value":"2020-12-14"},"_buckets":{"deposit":"2bcbc634-d581-417d-a406-d8e806195ff9"},"_deposit":{"id":"208942","pid":{"type":"depid","value":"208942","revision_id":0},"owners":[44499],"status":"published","created_by":44499},"item_title":"セキュアマルチパーティ計算によるエッジシステム上のBP学習法の提案","author_link":["525419","525417","525418","525420"],"item_titles":{"attribute_name":"タイトル","attribute_value_mlt":[{"subitem_title":"セキュアマルチパーティ計算によるエッジシステム上のBP学習法の提案"},{"subitem_title":"Proposal of BP learning with IoT using Secure Multiparty Computation","subitem_title_language":"en"}]},"item_keyword":{"attribute_name":"キーワード","attribute_value_mlt":[{"subitem_subject":"最適化","subitem_subject_scheme":"Other"}]},"item_type_id":"4","publish_date":"2020-12-14","item_4_text_3":{"attribute_name":"著者所属","attribute_value_mlt":[{"subitem_text_value":"長崎大学"},{"subitem_text_value":"鹿児島大学"},{"subitem_text_value":"鹿児島大学"},{"subitem_text_value":"中央大学"}]},"item_4_text_4":{"attribute_name":"著者所属(英)","attribute_value_mlt":[{"subitem_text_value":"Nagasaki University","subitem_text_language":"en"},{"subitem_text_value":"Kagoshima University","subitem_text_language":"en"},{"subitem_text_value":"Kagoshima University","subitem_text_language":"en"},{"subitem_text_value":"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/208942/files/IPSJ-DPS20185013.pdf","label":"IPSJ-DPS20185013.pdf"},"date":[{"dateType":"Available","dateValue":"2022-12-14"}],"format":"application/pdf","billing":["billing_file"],"filename":"IPSJ-DPS20185013.pdf","filesize":[{"value":"1.0 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":"34"},{"tax":["include_tax"],"price":"0","billingrole":"44"}],"accessrole":"open_date","version_id":"eca103e1-1e6f-47a2-8641-e1e2d4e6dfb8","displaytype":"detail","licensetype":"license_note","license_note":"Copyright (c) 2020 by the Information Processing Society of Japan"}]},"item_4_creator_5":{"attribute_name":"著者名","attribute_type":"creator","attribute_value_mlt":[{"creatorNames":[{"creatorName":"宮島, 洋文"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"重井, 徳貴"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"宮島, 廣美"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"白鳥, 則郎"}],"nameIdentifiers":[{}]}]},"item_4_source_id_9":{"attribute_name":"書誌レコードID","attribute_value_mlt":[{"subitem_source_identifier":"AN10116224","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":"2188-8906","subitem_source_identifier_type":"ISSN"}]},"item_4_description_7":{"attribute_name":"論文抄録","attribute_value_mlt":[{"subitem_description":"クラウドシステムのサーバの負担軽減の観点から，エッジシステムが提案されている．エッジステム上で安全に機械学習を行ういくつかのモデルが提案されている．その多くは，データを部分集合に分割して，部分計算とその統合を繰り返すものであり，データ自身を使って更新を行う．本稿では，秘匿性を高めるため，あらかじめデータ自身を分解しておき，これら分解したデータを使った BP 学習法を提案する．また，数値シミュレーションで，その有効性を示す．","subitem_description_type":"Other"}]},"item_4_biblio_info_10":{"attribute_name":"書誌情報","attribute_value_mlt":[{"bibliographicPageEnd":"7","bibliographic_titles":[{"bibliographic_title":"研究報告マルチメディア通信と分散処理（DPS）"}],"bibliographicPageStart":"1","bibliographicIssueDates":{"bibliographicIssueDate":"2020-12-14","bibliographicIssueDateType":"Issued"},"bibliographicIssueNumber":"13","bibliographicVolumeNumber":"2020-DPS-185"}]},"relation_version_is_last":true,"weko_creator_id":"44499"},"created":"2025-01-19T01:10:17.235597+00:00","id":208942,"links":{}}