{"created":"2023-07-27T06:24:29.096729+00:00","id":7407,"links":{},"metadata":{"_buckets":{"deposit":"24df73de-f3a6-40dc-adcd-0c99e463163e"},"_deposit":{"created_by":3,"id":"7407","owners":[3],"pid":{"revision_id":0,"type":"depid","value":"7407"},"status":"published"},"_oai":{"id":"oai:kanazawa-u.repo.nii.ac.jp:00007407","sets":["934:935:936"]},"author_link":["9785","353","9786"],"item_8_biblio_info_8":{"attribute_name":"書誌情報","attribute_value_mlt":[{"bibliographicIssueDates":{"bibliographicIssueDate":"1997-06-01","bibliographicIssueDateType":"Issued"},"bibliographicPageEnd":"1900","bibliographicPageStart":"1896","bibliographic_titles":[{"bibliographic_title":"IEEE International Conference on Neural Networks - Conference Proceedings"}]}]},"item_8_description_21":{"attribute_name":"抄録","attribute_value_mlt":[{"subitem_description":"The effects of the quantization of the parameters of a learning machine are discussed. The learning coefficient should be as small as possible for a better estimate of parameters. On the other hand, when the parameters are quantized, it should be relatively larger in order to avoid the paralysis of learning originated from the quantization. How to choose the learning coefficient is given in this paper from the statistical point of view.","subitem_description_type":"Abstract"}]},"item_8_publisher_17":{"attribute_name":"出版者","attribute_value_mlt":[{"subitem_publisher":"IEEE(Institute of Electrical and Electronics Engineers)"}]},"item_8_source_id_9":{"attribute_name":"ISSN","attribute_value_mlt":[{"subitem_source_identifier":"1098-7576","subitem_source_identifier_type":"ISSN"}]},"item_8_version_type_25":{"attribute_name":"著者版フラグ","attribute_value_mlt":[{"subitem_version_resource":"http://purl.org/coar/version/c_970fb48d4fbd8a85","subitem_version_type":"VoR"}]},"item_creator":{"attribute_name":"著者","attribute_type":"creator","attribute_value_mlt":[{"creatorNames":[{"creatorName":"Ikeda, Kazushi"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"Suzuki, Akihiro"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"Nakayama, Kenji"}],"nameIdentifiers":[{},{},{}]}]},"item_files":{"attribute_name":"ファイル情報","attribute_type":"file","attribute_value_mlt":[{"accessrole":"open_date","date":[{"dateType":"Available","dateValue":"2017-10-03"}],"displaytype":"detail","filename":"TE-PR-NAKAYAMA-K-1896.pdf","filesize":[{"value":"400.3 kB"}],"format":"application/pdf","licensetype":"license_note","mimetype":"application/pdf","url":{"label":"TE-PR-NAKAYAMA-K-1896.pdf","url":"https://kanazawa-u.repo.nii.ac.jp/record/7407/files/TE-PR-NAKAYAMA-K-1896.pdf"},"version_id":"b1fa2a33-42d5-459f-b7a3-e2c7b223e4d6"}]},"item_language":{"attribute_name":"言語","attribute_value_mlt":[{"subitem_language":"eng"}]},"item_resource_type":{"attribute_name":"資源タイプ","attribute_value_mlt":[{"resourcetype":"conference paper","resourceuri":"http://purl.org/coar/resource_type/c_5794"}]},"item_title":"The effects of quantization on the backpropagation learning","item_titles":{"attribute_name":"タイトル","attribute_value_mlt":[{"subitem_title":"The effects of quantization on the backpropagation learning"}]},"item_type_id":"8","owner":"3","path":["936"],"pubdate":{"attribute_name":"公開日","attribute_value":"2017-10-03"},"publish_date":"2017-10-03","publish_status":"0","recid":"7407","relation_version_is_last":true,"title":["The effects of quantization on the backpropagation learning"],"weko_creator_id":"3","weko_shared_id":-1},"updated":"2023-07-28T02:23:54.400084+00:00"}