{"created":"2025-01-19T01:15:26.412530+00:00","updated":"2025-01-19T16:32:25.390356+00:00","metadata":{"_oai":{"id":"oai:ipsj.ixsq.nii.ac.jp:00214633","sets":["6504:10735:10736"]},"path":["10736"],"owner":"44499","recid":"214633","title":["低ランク近似技法の深層学習への適用"],"pubdate":{"attribute_name":"公開日","attribute_value":"2021-03-04"},"_buckets":{"deposit":"c604d253-6f51-4607-8853-c6e1055c0935"},"_deposit":{"id":"214633","pid":{"type":"depid","value":"214633","revision_id":0},"owners":[44499],"status":"published","created_by":44499},"item_title":"低ランク近似技法の深層学習への適用","author_link":["551762"],"item_titles":{"attribute_name":"タイトル","attribute_value_mlt":[{"subitem_title":"低ランク近似技法の深層学習への適用"}]},"item_keyword":{"attribute_name":"キーワード","attribute_value_mlt":[{"subitem_subject":"コンピュータシステム","subitem_subject_scheme":"Other"}]},"item_type_id":"22","publish_date":"2021-03-04","item_language":{"attribute_name":"言語","attribute_value_mlt":[{"subitem_language":"jpn"}]},"item_22_text_3":{"attribute_name":"著者所属","attribute_value_mlt":[{"subitem_text_value":"山梨大"}]},"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/214633/files/IPSJ-Z83-2H-05.pdf","label":"IPSJ-Z83-2H-05.pdf"},"date":[{"dateType":"Available","dateValue":"2021-12-28"}],"format":"application/pdf","filename":"IPSJ-Z83-2H-05.pdf","filesize":[{"value":"226.8 kB"}],"mimetype":"application/pdf","accessrole":"open_date","version_id":"415e631c-02b8-47c7-b617-25dc278dbe84","displaytype":"detail","licensetype":"license_note","license_note":"Copyright (c) 2021 by the Information Processing Society of Japan"}]},"item_22_creator_5":{"attribute_name":"著者名","attribute_type":"creator","attribute_value_mlt":[{"creatorNames":[{"creatorName":"板垣, 翼"}],"nameIdentifiers":[{}]}]},"item_resource_type":{"attribute_name":"資源タイプ","attribute_value_mlt":[{"resourceuri":"http://purl.org/coar/resource_type/c_5794","resourcetype":"conference paper"}]},"item_22_source_id_9":{"attribute_name":"書誌レコードID","attribute_value_mlt":[{"subitem_source_identifier":"AN00349328","subitem_source_identifier_type":"NCID"}]},"item_22_description_7":{"attribute_name":"論文抄録","attribute_value_mlt":[{"subitem_description":"深層学習の登場は画像処理や自然言語処理などの各分野を大きく発展させている．そこで扱うタスクの複雑化は深層ニューラルネットワーク（DNN）や畳み込みニューラルネットワーク（CNN）を始めとしたモデルの複雑化を招き，重みパラメータの増大に繋がるが，近年ではスパースモデリングというモデル圧縮技術により改善されてきた．一方でモデルへ与える入力データの圧縮化に関してはあまり研究が行われていない．本研究では深層学習モデルに与える入力データの効率的な圧縮方法として，行列の近似圧縮技術として用いられている低ランク近似技法を利用した圧縮方法を試みその性能を調査した．","subitem_description_type":"Other"}]},"item_22_biblio_info_10":{"attribute_name":"書誌情報","attribute_value_mlt":[{"bibliographicPageEnd":"40","bibliographic_titles":[{"bibliographic_title":"第83回全国大会講演論文集"}],"bibliographicPageStart":"39","bibliographicIssueDates":{"bibliographicIssueDate":"2021-03-04","bibliographicIssueDateType":"Issued"},"bibliographicIssueNumber":"1","bibliographicVolumeNumber":"2021"}]},"relation_version_is_last":true,"weko_creator_id":"44499"},"id":214633,"links":{}}