{"created":"2025-01-19T00:22:24.218238+00:00","updated":"2025-01-20T17:43:07.460485+00:00","metadata":{"_oai":{"id":"oai:ipsj.ixsq.nii.ac.jp:00147184","sets":["1164:4619:8450:8451"]},"path":["8451"],"owner":"11","recid":"147184","title":["半教師付き学習におけるベイズ基準のもと最適な予測の計算量削減方法に関する一考察"],"pubdate":{"attribute_name":"公開日","attribute_value":"2016-01-14"},"_buckets":{"deposit":"263045c1-3d9c-42b4-8cc5-40ced72d2f87"},"_deposit":{"id":"147184","pid":{"type":"depid","value":"147184","revision_id":0},"owners":[11],"status":"published","created_by":11},"item_title":"半教師付き学習におけるベイズ基準のもと最適な予測の計算量削減方法に関する一考察","author_link":["232974","232973","232971","232972","232975","232976"],"item_titles":{"attribute_name":"タイトル","attribute_value_mlt":[{"subitem_title":"半教師付き学習におけるベイズ基準のもと最適な予測の計算量削減方法に関する一考察"},{"subitem_title":"A Note on the Computational Complexity Reduction Method of the Optimal Prediction under Bayes Criterion in Semi-Supervised Learning","subitem_title_language":"en"}]},"item_type_id":"4","publish_date":"2016-01-14","item_4_text_3":{"attribute_name":"著者所属","attribute_value_mlt":[{"subitem_text_value":"早稲田大学基幹理工学研究科数学応用数理専攻"},{"subitem_text_value":"早稲田大学基幹理工学研究科数学応用数理専攻"},{"subitem_text_value":"早稲田大学基幹理工学研究科数学応用数理専攻"}]},"item_4_text_4":{"attribute_name":"著者所属(英)","attribute_value_mlt":[{"subitem_text_value":"Department of Mathematics and Applied Mathematics, Graduate School of Fundamental Science and Engineering, Waseda University","subitem_text_language":"en"},{"subitem_text_value":"Department of Mathematics and Applied Mathematics, Graduate School of Fundamental Science and Engineering, Waseda University","subitem_text_language":"en"},{"subitem_text_value":"Department of Mathematics and Applied Mathematics, Graduate School of Fundamental Science and Engineering, Waseda 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/147184/files/IPSJ-CVIM16200044.pdf","label":"IPSJ-CVIM16200044.pdf"},"format":"application/pdf","billing":["billing_file"],"filename":"IPSJ-CVIM16200044.pdf","filesize":[{"value":"453.3 kB"}],"mimetype":"application/pdf","priceinfo":[{"tax":["include_tax"],"price":"0","billingrole":"20"},{"tax":["include_tax"],"price":"0","billingrole":"44"}],"accessrole":"open_login","version_id":"1b86b2dd-d79b-4cf3-98ec-4ac9d6becd59","displaytype":"detail","licensetype":"license_note","license_note":"Copyright (c) 2016 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":"中野, 雄斗"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"齋藤, 翔太"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"松嶋, 敏泰"}],"nameIdentifiers":[{}]}]},"item_4_creator_6":{"attribute_name":"著者名(英)","attribute_type":"creator","attribute_value_mlt":[{"creatorNames":[{"creatorName":"Yuto, Nakano","creatorNameLang":"en"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"Shota, Saito","creatorNameLang":"en"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"Toshiyasu, Matsushima","creatorNameLang":"en"}],"nameIdentifiers":[{}]}]},"item_4_source_id_9":{"attribute_name":"書誌レコードID","attribute_value_mlt":[{"subitem_source_identifier":"AA11131797","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":"2188-8701","subitem_source_identifier_type":"ISSN"}]},"item_4_description_7":{"attribute_name":"論文抄録","attribute_value_mlt":[{"subitem_description":"本稿では，統計的決定理論に基づく半教師付き学習における予測問題を扱う．この問題に対して，従来ベイズ基準のもとで最適なデータ予測に関する定式化が行われている．しかし，ベイズ基準のもと最適な予測は，未知のデータ数に対し指数的に計算量が増大するという問題がある．そこで本研究では計算量を削減するために，EM アルゴリズム用いて未知のデータ集合を近似するアルゴリズムを用い，シミュレーションにより予測精度を検証する．","subitem_description_type":"Other"}]},"item_4_description_8":{"attribute_name":"論文抄録(英)","attribute_value_mlt":[{"subitem_description":"In this paper, we deal with a prediction problem of the semi-supervised learning based on the statistical decision theory. Previous study has formulated the optimal data prediction under Bayes criterion. However, the computational complexity of this method grows exponentially with the number of the unknown data. This study applies an approximation algorithm reducing the computational complexity using EM algorithm and evaluates this algorithm through simulations.","subitem_description_type":"Other"}]},"item_4_biblio_info_10":{"attribute_name":"書誌情報","attribute_value_mlt":[{"bibliographicPageEnd":"6","bibliographic_titles":[{"bibliographic_title":"研究報告コンピュータビジョンとイメージメディア（CVIM）"}],"bibliographicPageStart":"1","bibliographicIssueDates":{"bibliographicIssueDate":"2016-01-14","bibliographicIssueDateType":"Issued"},"bibliographicIssueNumber":"44","bibliographicVolumeNumber":"2016-CVIM-200"}]},"relation_version_is_last":true,"weko_creator_id":"11"},"id":147184,"links":{}}