{"id":"https://openalex.org/W1546315089","doi":"https://doi.org/10.1007/978-3-642-10677-4_54","title":"Optimal Hyperparameters for Generalized Learning and Knowledge Discovery in Variational Bayes","display_name":"Optimal Hyperparameters for Generalized Learning and Knowledge Discovery in Variational Bayes","publication_year":2009,"publication_date":"2009-01-01","ids":{"openalex":"https://openalex.org/W1546315089","doi":"https://doi.org/10.1007/978-3-642-10677-4_54","mag":"1546315089"},"language":"en","primary_location":{"id":"doi:10.1007/978-3-642-10677-4_54","is_oa":false,"landing_page_url":"https://doi.org/10.1007/978-3-642-10677-4_54","pdf_url":null,"source":{"id":"https://openalex.org/S106296714","display_name":"Lecture notes in computer science","issn_l":"0302-9743","issn":["0302-9743","1611-3349"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319900","host_organization_name":"Springer Science+Business Media","host_organization_lineage":["https://openalex.org/P4310319900","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Science+Business Media","Springer Nature"],"type":"book series"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Lecture Notes in Computer Science","raw_type":"book-chapter"},"type":"book-chapter","indexed_in":["crossref"],"open_access":{"is_oa":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5014635641","display_name":"Daisuke Kaji","orcid":null},"institutions":[{"id":"https://openalex.org/I114531698","display_name":"Tokyo Institute of Technology","ror":"https://ror.org/0112mx960","country_code":"JP","type":"education","lineage":["https://openalex.org/I114531698"]},{"id":"https://openalex.org/I4210094737","display_name":"Tokyo Medical University Hachioji Medical Center","ror":"https://ror.org/00vpv1x26","country_code":"JP","type":"healthcare","lineage":["https://openalex.org/I4210094737"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Daisuke Kaji","raw_affiliation_strings":["Computational Intelligence and System Science, Tokyo Institute of Technology, Mailbox R2-5, 4259 Nagatsuda, Midori-ku, Yokohama, 226-8503, Japan","Konicaminolta Medical and Graphic, INC., 2970 Ishikawa-machi, Hachioji-shi, Tokyo, 192-8505, Japan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Computational Intelligence and System Science, Tokyo Institute of Technology, Mailbox R2-5, 4259 Nagatsuda, Midori-ku, Yokohama, 226-8503, Japan","institution_ids":["https://openalex.org/I114531698"]},{"raw_affiliation_string":"Konicaminolta Medical and Graphic, INC., 2970 Ishikawa-machi, Hachioji-shi, Tokyo, 192-8505, Japan","institution_ids":["https://openalex.org/I4210094737"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5089768991","display_name":"Sumio Watanabe","orcid":"https://orcid.org/0000-0001-8341-5639"},"institutions":[{"id":"https://openalex.org/I114531698","display_name":"Tokyo Institute of Technology","ror":"https://ror.org/0112mx960","country_code":"JP","type":"education","lineage":["https://openalex.org/I114531698"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Sumio Watanabe","raw_affiliation_strings":["Precision and Intelligence Laboratory, Tokyo Institute of Technology, 4529 Nagatsuda, Midori-ku, Yokohama, 226-8503, Japan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Precision and Intelligence Laboratory, Tokyo Institute of Technology, 4529 Nagatsuda, Midori-ku, Yokohama, 226-8503, Japan","institution_ids":["https://openalex.org/I114531698"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":{"value":5000,"currency":"EUR","value_usd":5392},"apc_paid":null,"fwci":0.2891,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":{"value":0.56510067,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":94},"biblio":{"volume":null,"issue":null,"first_page":"476","last_page":"483"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12814","display_name":"Gaussian Processes and Bayesian Inference","score":0.9994999766349792,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T12814","display_name":"Gaussian Processes and Bayesian Inference","score":0.9994999766349792,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11901","display_name":"Bayesian Methods and Mixture Models","score":0.9979000091552734,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T12072","display_name":"Machine Learning and Algorithms","score":0.9901000261306763,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/hyperparameter","display_name":"Hyperparameter","score":0.9605863094329834},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.684553861618042},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.6244162917137146},{"id":"https://openalex.org/keywords/maximum-a-posteriori-estimation","display_name":"Maximum a posteriori estimation","score":0.5857608318328857},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5824559926986694},{"id":"https://openalex.org/keywords/bayes-theorem","display_name":"Bayes' theorem","score":0.5436614155769348},{"id":"https://openalex.org/keywords/binomial","display_name":"Binomial (polynomial)","score":0.4288565218448639},{"id":"https://openalex.org/keywords/a-priori-and-a-posteriori","display_name":"A priori and a posteriori","score":0.419596403837204},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3604327440261841},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.32122915983200073},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.2527333199977875},{"id":"https://openalex.org/keywords/bayesian-probability","display_name":"Bayesian probability","score":0.22408846020698547},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.12858429551124573},{"id":"https://openalex.org/keywords/maximum-likelihood","display_name":"Maximum likelihood","score":0.06957221031188965}],"concepts":[{"id":"https://openalex.org/C8642999","wikidata":"https://www.wikidata.org/wiki/Q4171168","display_name":"Hyperparameter","level":2,"score":0.9605863094329834},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.684553861618042},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.6244162917137146},{"id":"https://openalex.org/C9810830","wikidata":"https://www.wikidata.org/wiki/Q635384","display_name":"Maximum a posteriori estimation","level":3,"score":0.5857608318328857},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5824559926986694},{"id":"https://openalex.org/C207201462","wikidata":"https://www.wikidata.org/wiki/Q182505","display_name":"Bayes' theorem","level":3,"score":0.5436614155769348},{"id":"https://openalex.org/C2781315470","wikidata":"https://www.wikidata.org/wiki/Q193623","display_name":"Binomial (polynomial)","level":2,"score":0.4288565218448639},{"id":"https://openalex.org/C75553542","wikidata":"https://www.wikidata.org/wiki/Q178161","display_name":"A priori and a posteriori","level":2,"score":0.419596403837204},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3604327440261841},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.32122915983200073},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.2527333199977875},{"id":"https://openalex.org/C107673813","wikidata":"https://www.wikidata.org/wiki/Q812534","display_name":"Bayesian probability","level":2,"score":0.22408846020698547},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.12858429551124573},{"id":"https://openalex.org/C49781872","wikidata":"https://www.wikidata.org/wiki/Q1045555","display_name":"Maximum likelihood","level":2,"score":0.06957221031188965},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C111472728","wikidata":"https://www.wikidata.org/wiki/Q9471","display_name":"Epistemology","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1007/978-3-642-10677-4_54","is_oa":false,"landing_page_url":"https://doi.org/10.1007/978-3-642-10677-4_54","pdf_url":null,"source":{"id":"https://openalex.org/S106296714","display_name":"Lecture notes in computer science","issn_l":"0302-9743","issn":["0302-9743","1611-3349"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319900","host_organization_name":"Springer Science+Business Media","host_organization_lineage":["https://openalex.org/P4310319900","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Science+Business Media","Springer Nature"],"type":"book series"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Lecture Notes in Computer Science","raw_type":"book-chapter"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":16,"referenced_works":["https://openalex.org/W1594725708","https://openalex.org/W1608094059","https://openalex.org/W1618600317","https://openalex.org/W1663973292","https://openalex.org/W2001689396","https://openalex.org/W2004748399","https://openalex.org/W2009086942","https://openalex.org/W2014927347","https://openalex.org/W2030085689","https://openalex.org/W2107743791","https://openalex.org/W2115979064","https://openalex.org/W2120217353","https://openalex.org/W2132474962","https://openalex.org/W2554987453","https://openalex.org/W4233135949","https://openalex.org/W4248597109"],"related_works":["https://openalex.org/W2140186469","https://openalex.org/W4390421286","https://openalex.org/W4280563792","https://openalex.org/W2903921062","https://openalex.org/W2150865841","https://openalex.org/W4309133645","https://openalex.org/W2138865713","https://openalex.org/W2169353922","https://openalex.org/W270990291","https://openalex.org/W2465532522"],"abstract_inverted_index":null,"counts_by_year":[{"year":2013,"cited_by_count":1}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}