{"id":190713,"updated":"2025-01-20T01:06:11.515401+00:00","links":{},"created":"2025-01-19T00:56:39.921578+00:00","metadata":{"_oai":{"id":"oai:ipsj.ixsq.nii.ac.jp:00190713","sets":["1164:1579:9341:9527"]},"path":["9527"],"owner":"11","recid":"190713","title":["FPGA を用いたオンライン逐次学習による教師無し異常検知のための高効率化と安定化手法"],"pubdate":{"attribute_name":"公開日","attribute_value":"2018-07-23"},"_buckets":{"deposit":"1d8f52ca-7dd9-47d3-8870-de9c98f854ba"},"_deposit":{"id":"190713","pid":{"type":"depid","value":"190713","revision_id":0},"owners":[11],"status":"published","created_by":11},"item_title":"FPGA を用いたオンライン逐次学習による教師無し異常検知のための高効率化と安定化手法","author_link":["437274","437271","437272","437273","437269","437270"],"item_titles":{"attribute_name":"タイトル","attribute_value_mlt":[{"subitem_title":"FPGA を用いたオンライン逐次学習による教師無し異常検知のための高効率化と安定化手法"},{"subitem_title":"A Stable and Efficient Learning Method for FPGA-Based Online Sequential Unsupervised Anomaly Detector","subitem_title_language":"en"}]},"item_keyword":{"attribute_name":"キーワード","attribute_value_mlt":[{"subitem_subject":"リコンフィギャラブルコンピューティング","subitem_subject_scheme":"Other"}]},"item_type_id":"4","publish_date":"2018-07-23","item_4_text_3":{"attribute_name":"著者所属","attribute_value_mlt":[{"subitem_text_value":"慶應義塾大学大学院理工学研究科"},{"subitem_text_value":"東京大学大学院情報理工学系研究科"},{"subitem_text_value":"慶應義塾大学大学院理工学研究科"}]},"item_4_text_4":{"attribute_name":"著者所属(英)","attribute_value_mlt":[{"subitem_text_value":"Graduate School of Science and Technology, Keio University","subitem_text_language":"en"},{"subitem_text_value":"Graduate School of Information Science and Technology, The University of Tokyo","subitem_text_language":"en"},{"subitem_text_value":"Graduate School of Science and Technology, Keio 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/190713/files/IPSJ-ARC18232031.pdf","label":"IPSJ-ARC18232031.pdf"},"format":"application/pdf","billing":["billing_file"],"filename":"IPSJ-ARC18232031.pdf","filesize":[{"value":"906.6 kB"}],"mimetype":"application/pdf","priceinfo":[{"tax":["include_tax"],"price":"0","billingrole":"16"},{"tax":["include_tax"],"price":"0","billingrole":"44"}],"accessrole":"open_login","version_id":"40da7836-070e-4ae6-b736-ccd4f7c53a8f","displaytype":"detail","licensetype":"license_note","license_note":"Copyright (c) 2018 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":"塚田, 峰登"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"近藤, 正章"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"松谷, 宏紀"}],"nameIdentifiers":[{}]}]},"item_4_creator_6":{"attribute_name":"著者名(英)","attribute_type":"creator","attribute_value_mlt":[{"creatorNames":[{"creatorName":"Mineto, Tsukada","creatorNameLang":"en"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"Masaaki, Kondo","creatorNameLang":"en"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"Hiroki, Matsutani","creatorNameLang":"en"}],"nameIdentifiers":[{}]}]},"item_4_source_id_9":{"attribute_name":"書誌レコードID","attribute_value_mlt":[{"subitem_source_identifier":"AN10096105","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":"2188-8574","subitem_source_identifier_type":"ISSN"}]},"item_4_description_7":{"attribute_name":"論文抄録","attribute_value_mlt":[{"subitem_description":"近年，教師無しオンライン異常検知が注目を集めている．この手法は入力データを逐次的に学習するため，入力データの特徴の時系列変化に追随しながら異常データを検知できる．関連する最新の研究の 1 つとして，逐次学習アルゴリズム OS-ELM と，ニューラルネットワーク技術の 1 のオートエンコーダーを組み合わせた高効率な FPGA ベースの異常検知器が提案されており，バッチサイズを 1 に固定することで小さな面積で高いスループットを実現している．しかし，バッチサイズを 1 に固定すると他の入力サンプルとの相対的な情報が得られず，異常データの除去が困難になる．また，上記異常検知器は忘却機能を備えておらず，入力データの特徴の時系列変化が生じる度に精度が低下する．そこで本論文では，極めて低コストな忘却手法とキューを用いた異常データの除去手法を提案する．本論文の評価で，非定常環境における分類問題と回帰問題において，それぞれ 1.6% の正答率の低下と 1.4% の平均損失値の上昇を許容することで，全 FPGA リソースにおいて 1% 未満の面積オーバーヘッド忘却機構を実装できることを示した．また，上記の 2 手法を組み合わせた異常検知器は全 FPGA リソースにおいて 10% 以下の面積オーバーヘッドで実装でき，非定常環境における異常検知問題に対して有効であることを示した．","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・アーキテクチャ（ARC）"}],"bibliographicPageStart":"1","bibliographicIssueDates":{"bibliographicIssueDate":"2018-07-23","bibliographicIssueDateType":"Issued"},"bibliographicIssueNumber":"31","bibliographicVolumeNumber":"2018-ARC-232"}]},"relation_version_is_last":true,"weko_creator_id":"11"}}