{"metadata":{"_oai":{"id":"oai:ipsj.ixsq.nii.ac.jp:00191362","sets":["1164:4619:9352:9559"]},"path":["9559"],"owner":"11","recid":"191362","title":["混合型分布族のMDL学習に関する考察"],"pubdate":{"attribute_name":"公開日","attribute_value":"2018-09-13"},"_buckets":{"deposit":"d690dce8-26a7-403d-93a4-a3442f93b33c"},"_deposit":{"id":"191362","pid":{"type":"depid","value":"191362","revision_id":0},"owners":[11],"status":"published","created_by":11},"item_title":"混合型分布族のMDL学習に関する考察","author_link":["441111","441110","441109","441112"],"item_titles":{"attribute_name":"タイトル","attribute_value_mlt":[{"subitem_title":"混合型分布族のMDL学習に関する考察"},{"subitem_title":"A Study on MDL Learning of Mixture Families","subitem_title_language":"en"}]},"item_keyword":{"attribute_name":"キーワード","attribute_value_mlt":[{"subitem_subject":"ディスカッションセッション3","subitem_subject_scheme":"Other"}]},"item_type_id":"4","publish_date":"2018-09-13","item_4_text_3":{"attribute_name":"著者所属","attribute_value_mlt":[{"subitem_text_value":"九州大学大学院システム情報科学府"},{"subitem_text_value":"九州大学大学院システム情報科学研究院"}]},"item_4_text_4":{"attribute_name":"著者所属(英)","attribute_value_mlt":[{"subitem_text_value":"Graduate School of Information Science and Electrical Engineering, Kyushu University","subitem_text_language":"en"},{"subitem_text_value":"Faculty of Information Science and Electrical Engineering, Kyushu 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/191362/files/IPSJ-CVIM18213017.pdf","label":"IPSJ-CVIM18213017.pdf"},"format":"application/pdf","billing":["billing_file"],"filename":"IPSJ-CVIM18213017.pdf","filesize":[{"value":"383.1 kB"}],"mimetype":"application/pdf","priceinfo":[{"tax":["include_tax"],"price":"0","billingrole":"20"},{"tax":["include_tax"],"price":"0","billingrole":"44"}],"accessrole":"open_login","version_id":"9829deca-8b8b-43d0-b253-143dd39d8ed9","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":"宮本, 耕平"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"竹内, 純一"}],"nameIdentifiers":[{}]}]},"item_4_creator_6":{"attribute_name":"著者名(英)","attribute_type":"creator","attribute_value_mlt":[{"creatorNames":[{"creatorName":"Kohei, Miyamoto","creatorNameLang":"en"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"Jun'ichi, Takeuchi","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":"記述長最小原理 (MDL 原理) に基づいたパラメータ推定の方法として，二段階符号によって定義される MDL 推定量がある．MDL 推定量の性能に関して，Barron and Cover による符号の冗長度によってリスク上界を与える理論が知られている．冗長度の評価について，モデルが指数型分布族の場合には既に，最適なユニバーサル符号のリグレットであるミニマックスリグレットに近い値を達成する二段階符号が知られているが，指数型分布族以外のモデルに関しては未解決である．本稿では非指数型分布族として混合型分布族を対象とし，Bayes 符号によりミニマックスリグレットを達成するために用いられた局所指数族バンドルに基づく手法を二段階符号の冗長度評価に応用した．結果として，混合成分数が 2 つの混合型分布族の MDL 推定量について，指数型分布族の場合と同等なリスク上界を得た．","subitem_description_type":"Other"}]},"item_4_description_8":{"attribute_name":"論文抄録(英)","attribute_value_mlt":[{"subitem_description":"MDL estimators based on two stage codes are studied. The Barren and Cover's theory shows that redundancy of a two stage code bounds the risk of the MDL estimator defined by the two stage code. It is known that coding regret of two stage codes for exponential families can be close to the minimax regret, which is related to stochastic complexity, while it is not for non-exponential families. I this paper, we propose a new method of two stage codes for two components mixture families, whose regret can be close to the minimax regret. The method is based on local exponential family bundles, which are used to evaluate the minimax regret for non-exponential families. Further, we obtain a tight risk bound of MDL estimators for mixture families.","subitem_description_type":"Other"}]},"item_4_biblio_info_10":{"attribute_name":"書誌情報","attribute_value_mlt":[{"bibliographicPageEnd":"8","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":"2018-09-13","bibliographicIssueDateType":"Issued"},"bibliographicIssueNumber":"17","bibliographicVolumeNumber":"2018-CVIM-213"}]},"relation_version_is_last":true,"weko_creator_id":"11"},"id":191362,"updated":"2025-01-20T00:43:05.725295+00:00","links":{},"created":"2025-01-19T00:57:15.341226+00:00"}