{"id":{"repo_id":"kyoto","oai_identifier":"oai:repository.kulib.kyoto-u.ac.jp:2433/266686"},"canonical_url":"https://search.dev.ndltd.org/etd/kyoto/oai:repository.kulib.kyoto-u.ac.jp:2433/266686","repository":{"repo_id":"kyoto","name":"Kyoto University","base_url":"https://repository.kulib.kyoto-u.ac.jp/server/oai/request"},"display":{"title":"Scalable Estimation on Linear and Nonlinear Regression Models via Decentralized Processing: Adaptive LMS Filter and Gaussian Process Regression","abstract":"","abstract_html":null,"abstract_has_math":false,"creators":["Nakai, Ayano"],"institution":"Kyoto University","degree_name":null,"degree_level":null,"degree_discipline":null,"degree_department":null,"school":null,"contributors":[],"advisors":[],"committee_chairs":[],"committee_members":[],"year":2021,"date_issued":"2021-11-24","date_published":"2021-11-24","updated_at":"2026-07-24T02:47:58Z","subjects":["Decentralized processing","Adaptive filters","Gaussian process regression","Scalability","Linear sketching"],"languages":["eng"],"rights":["学位規則第9条第2項により要約公開","許諾条件により本文は2024-06-12に公開","In reference to IEEE copyrighted material which is used with permission in this thesis, the IEEE does not endorse any of Kyoto University’s products or services. 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