{"id":"https://openalex.org/W3003971345","doi":"https://doi.org/10.5555/1756006.1953035","title":"Approximate Riemannian Conjugate Gradient Learning for Fixed-Form Variational Bayes","display_name":"Approximate Riemannian Conjugate Gradient Learning for Fixed-Form Variational Bayes","publication_year":2010,"publication_date":"2010-12-01","ids":{"openalex":"https://openalex.org/W3003971345","doi":"https://doi.org/10.5555/1756006.1953035","mag":"3003971345"},"language":"en","primary_location":{"id":"mag:3003971345","is_oa":false,"landing_page_url":"https://dl.acm.org/doi/10.5555/1756006.1953035","pdf_url":null,"source":{"id":"https://openalex.org/S118988714","display_name":"Journal of Machine Learning Research","issn_l":"1532-4435","issn":["1532-4435","1533-7928"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310315718","host_organization_name":"The MIT Press","host_organization_lineage":["https://openalex.org/P4310315718","https://openalex.org/P4310316440"],"host_organization_lineage_names":["The MIT Press","Massachusetts Institute of Technology"],"type":"journal"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false,"raw_source_name":"Journal of Machine Learning Research","raw_type":null},"type":"article","indexed_in":[],"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/A5043777807","display_name":"HonkelaAntti","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"HonkelaAntti","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5030789376","display_name":"RaikoTapani","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"RaikoTapani","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5090306350","display_name":"KuuselaMikael","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"KuuselaMikael","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5027587812","display_name":"TornioMatti","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"TornioMatti","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5088106471","display_name":"KarhunenJuha","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"KarhunenJuha","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":0,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.41750285,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":94},"biblio":{"volume":null,"issue":null,"first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12814","display_name":"Gaussian Processes and Bayesian Inference","score":0.9898999929428101,"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":0.9898999929428101,"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/T11307","display_name":"Domain Adaptation and Few-Shot Learning","score":0.9689000248908997,"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":0.9412000179290771,"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/mathematics","display_name":"Mathematics","score":0.6094326972961426},{"id":"https://openalex.org/keywords/conjugate-gradient-method","display_name":"Conjugate gradient method","score":0.6014422178268433},{"id":"https://openalex.org/keywords/applied-mathematics","display_name":"Applied mathematics","score":0.49872922897338867},{"id":"https://openalex.org/keywords/bayes-theorem","display_name":"Bayes' theorem","score":0.47447946667671204},{"id":"https://openalex.org/keywords/mathematical-optimization","display_name":"Mathematical optimization","score":0.38927149772644043},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.3533242642879486},{"id":"https://openalex.org/keywords/bayesian-probability","display_name":"Bayesian probability","score":0.24628260731697083},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.09525090456008911}],"concepts":[{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.6094326972961426},{"id":"https://openalex.org/C81184566","wikidata":"https://www.wikidata.org/wiki/Q1191895","display_name":"Conjugate gradient method","level":2,"score":0.6014422178268433},{"id":"https://openalex.org/C28826006","wikidata":"https://www.wikidata.org/wiki/Q33521","display_name":"Applied mathematics","level":1,"score":0.49872922897338867},{"id":"https://openalex.org/C207201462","wikidata":"https://www.wikidata.org/wiki/Q182505","display_name":"Bayes' theorem","level":3,"score":0.47447946667671204},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.38927149772644043},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.3533242642879486},{"id":"https://openalex.org/C107673813","wikidata":"https://www.wikidata.org/wiki/Q812534","display_name":"Bayesian probability","level":2,"score":0.24628260731697083},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.09525090456008911}],"mesh":[],"locations_count":1,"locations":[{"id":"mag:3003971345","is_oa":false,"landing_page_url":"https://dl.acm.org/doi/10.5555/1756006.1953035","pdf_url":null,"source":{"id":"https://openalex.org/S118988714","display_name":"Journal of Machine Learning Research","issn_l":"1532-4435","issn":["1532-4435","1533-7928"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310315718","host_organization_name":"The MIT Press","host_organization_lineage":["https://openalex.org/P4310315718","https://openalex.org/P4310316440"],"host_organization_lineage_names":["The MIT Press","Massachusetts Institute of Technology"],"type":"journal"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":null,"raw_source_name":"Journal of Machine Learning Research","raw_type":null}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Reduced inequalities","score":0.4699999988079071,"id":"https://metadata.un.org/sdg/10"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":["https://openalex.org/W2883432777","https://openalex.org/W2761037722","https://openalex.org/W2134470445","https://openalex.org/W2612481336","https://openalex.org/W2407371555","https://openalex.org/W2118910129","https://openalex.org/W2131583078","https://openalex.org/W2136870201","https://openalex.org/W2141200443","https://openalex.org/W2942503084","https://openalex.org/W2963736577","https://openalex.org/W2028249695","https://openalex.org/W2963637370","https://openalex.org/W3125452207","https://openalex.org/W2124682120","https://openalex.org/W3176516134","https://openalex.org/W2963015795","https://openalex.org/W1987721624","https://openalex.org/W1580282541","https://openalex.org/W2914905650"],"abstract_inverted_index":{"Variational":[0],"Bayesian":[1,17],"(VB)":[2],"methods":[3],"are":[4],"typically":[5],"only":[6],"applied":[7],"to":[8],"models":[9],"in":[10],"the":[11,15],"conjugate-exponential":[12],"family":[13],"using":[14],"variational":[16],"expectation":[18],"maximisation":[19],"(VB":[20],"EM)":[21],"algorithm":[22],"or":[23],"one":[24],"of":[25],"its":[26],"va...":[27]},"counts_by_year":[{"year":2014,"cited_by_count":1}],"updated_date":"2026-08-15T07:11:24.734988","created_date":"2025-10-10T00:00:00"}
