{"id":"https://openalex.org/W208957287","doi":"https://doi.org/10.1007/978-3-319-03680-9_41","title":"Minimum Message Length Ridge Regression for Generalized Linear Models","display_name":"Minimum Message Length Ridge Regression for Generalized Linear Models","publication_year":2013,"publication_date":"2013-01-01","ids":{"openalex":"https://openalex.org/W208957287","doi":"https://doi.org/10.1007/978-3-319-03680-9_41","mag":"208957287"},"language":"en","primary_location":{"id":"doi:10.1007/978-3-319-03680-9_41","is_oa":false,"landing_page_url":"https://doi.org/10.1007/978-3-319-03680-9_41","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":"conference-paper","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/A5046316602","display_name":"Daniel F. Schmidt","orcid":"https://orcid.org/0000-0002-1788-2375"},"institutions":[{"id":"https://openalex.org/I165779595","display_name":"The University of Melbourne","ror":"https://ror.org/01ej9dk98","country_code":"AU","type":"education","lineage":["https://openalex.org/I165779595"]}],"countries":["AU"],"is_corresponding":false,"raw_author_name":"Daniel F. Schmidt","raw_affiliation_strings":["Centre for MEGA Epidemiology, The University of Melbourne, Carlton, VIC, 3053, Australia","Centre for MEGA Epidemiology, The University of Melbourne, Carlton, Australia#TAB#"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Centre for MEGA Epidemiology, The University of Melbourne, Carlton, VIC, 3053, Australia","institution_ids":["https://openalex.org/I165779595"]},{"raw_affiliation_string":"Centre for MEGA Epidemiology, The University of Melbourne, Carlton, Australia#TAB#","institution_ids":["https://openalex.org/I165779595"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5023193568","display_name":"Enes Makalic","orcid":"https://orcid.org/0000-0003-3017-0871"},"institutions":[{"id":"https://openalex.org/I165779595","display_name":"The University of Melbourne","ror":"https://ror.org/01ej9dk98","country_code":"AU","type":"education","lineage":["https://openalex.org/I165779595"]}],"countries":["AU"],"is_corresponding":false,"raw_author_name":"Enes Makalic","raw_affiliation_strings":["Centre for MEGA Epidemiology, The University of Melbourne, Carlton, VIC, 3053, Australia","Centre for MEGA Epidemiology, The University of Melbourne, Carlton, Australia#TAB#"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Centre for MEGA Epidemiology, The University of Melbourne, Carlton, VIC, 3053, Australia","institution_ids":["https://openalex.org/I165779595"]},{"raw_affiliation_string":"Centre for MEGA Epidemiology, The University of Melbourne, Carlton, Australia#TAB#","institution_ids":["https://openalex.org/I165779595"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I165779595"],"apc_list":{"value":5000,"currency":"EUR","value_usd":5392},"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":3,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"408","last_page":"420"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11901","display_name":"Bayesian Methods and Mixture Models","score":0.9984999895095825,"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/T11901","display_name":"Bayesian Methods and Mixture Models","score":0.9984999895095825,"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/T11871","display_name":"Advanced Statistical Methods and Models","score":0.9983999729156494,"subfield":{"id":"https://openalex.org/subfields/2613","display_name":"Statistics and Probability"},"field":{"id":"https://openalex.org/fields/26","display_name":"Mathematics"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10136","display_name":"Statistical Methods and Inference","score":0.9976999759674072,"subfield":{"id":"https://openalex.org/subfields/2613","display_name":"Statistics and Probability"},"field":{"id":"https://openalex.org/fields/26","display_name":"Mathematics"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/akaike-information-criterion","display_name":"Akaike information criterion","score":0.8936210870742798},{"id":"https://openalex.org/keywords/hyperparameter","display_name":"Hyperparameter","score":0.6289766430854797},{"id":"https://openalex.org/keywords/poisson-distribution","display_name":"Poisson distribution","score":0.6247729659080505},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6247363090515137},{"id":"https://openalex.org/keywords/model-selection","display_name":"Model selection","score":0.6106883883476257},{"id":"https://openalex.org/keywords/range","display_name":"Range (aeronautics)","score":0.6012851595878601},{"id":"https://openalex.org/keywords/generalized-linear-model","display_name":"Generalized linear model","score":0.6008412837982178},{"id":"https://openalex.org/keywords/bayesian-information-criterion","display_name":"Bayesian information criterion","score":0.5620797872543335},{"id":"https://openalex.org/keywords/information-criteria","display_name":"Information Criteria","score":0.5496174693107605},{"id":"https://openalex.org/keywords/poisson-regression","display_name":"Poisson regression","score":0.49145448207855225},{"id":"https://openalex.org/keywords/ridge","display_name":"Ridge","score":0.48625361919403076},{"id":"https://openalex.org/keywords/minimum-description-length","display_name":"Minimum description length","score":0.4732138216495514},{"id":"https://openalex.org/keywords/negative-binomial-distribution","display_name":"Negative binomial distribution","score":0.43451589345932007},{"id":"https://openalex.org/keywords/selection","display_name":"Selection (genetic algorithm)","score":0.4212300181388855},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.4066762924194336},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.39992403984069824},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.36966678500175476},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.28057172894477844},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.19688349962234497}],"concepts":[{"id":"https://openalex.org/C126674687","wikidata":"https://www.wikidata.org/wiki/Q1662573","display_name":"Akaike information criterion","level":2,"score":0.8936210870742798},{"id":"https://openalex.org/C8642999","wikidata":"https://www.wikidata.org/wiki/Q4171168","display_name":"Hyperparameter","level":2,"score":0.6289766430854797},{"id":"https://openalex.org/C100906024","wikidata":"https://www.wikidata.org/wiki/Q205692","display_name":"Poisson distribution","level":2,"score":0.6247729659080505},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6247363090515137},{"id":"https://openalex.org/C93959086","wikidata":"https://www.wikidata.org/wiki/Q6888345","display_name":"Model selection","level":2,"score":0.6106883883476257},{"id":"https://openalex.org/C204323151","wikidata":"https://www.wikidata.org/wiki/Q905424","display_name":"Range (aeronautics)","level":2,"score":0.6012851595878601},{"id":"https://openalex.org/C41587187","wikidata":"https://www.wikidata.org/wiki/Q1501882","display_name":"Generalized linear model","level":2,"score":0.6008412837982178},{"id":"https://openalex.org/C168136583","wikidata":"https://www.wikidata.org/wiki/Q1988242","display_name":"Bayesian information criterion","level":2,"score":0.5620797872543335},{"id":"https://openalex.org/C2776709221","wikidata":"https://www.wikidata.org/wiki/Q6031040","display_name":"Information Criteria","level":3,"score":0.5496174693107605},{"id":"https://openalex.org/C73269764","wikidata":"https://www.wikidata.org/wiki/Q954529","display_name":"Poisson regression","level":3,"score":0.49145448207855225},{"id":"https://openalex.org/C32277403","wikidata":"https://www.wikidata.org/wiki/Q740445","display_name":"Ridge","level":2,"score":0.48625361919403076},{"id":"https://openalex.org/C87465248","wikidata":"https://www.wikidata.org/wiki/Q1417790","display_name":"Minimum description length","level":2,"score":0.4732138216495514},{"id":"https://openalex.org/C199335787","wikidata":"https://www.wikidata.org/wiki/Q743364","display_name":"Negative binomial distribution","level":3,"score":0.43451589345932007},{"id":"https://openalex.org/C81917197","wikidata":"https://www.wikidata.org/wiki/Q628760","display_name":"Selection (genetic algorithm)","level":2,"score":0.4212300181388855},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.4066762924194336},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.39992403984069824},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.36966678500175476},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.28057172894477844},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.19688349962234497},{"id":"https://openalex.org/C149923435","wikidata":"https://www.wikidata.org/wiki/Q37732","display_name":"Demography","level":1,"score":0.0},{"id":"https://openalex.org/C151730666","wikidata":"https://www.wikidata.org/wiki/Q7205","display_name":"Paleontology","level":1,"score":0.0},{"id":"https://openalex.org/C192562407","wikidata":"https://www.wikidata.org/wiki/Q228736","display_name":"Materials science","level":0,"score":0.0},{"id":"https://openalex.org/C2908647359","wikidata":"https://www.wikidata.org/wiki/Q2625603","display_name":"Population","level":2,"score":0.0},{"id":"https://openalex.org/C144024400","wikidata":"https://www.wikidata.org/wiki/Q21201","display_name":"Sociology","level":0,"score":0.0},{"id":"https://openalex.org/C159985019","wikidata":"https://www.wikidata.org/wiki/Q181790","display_name":"Composite material","level":1,"score":0.0},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1007/978-3-319-03680-9_41","is_oa":false,"landing_page_url":"https://doi.org/10.1007/978-3-319-03680-9_41","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":18,"referenced_works":["https://openalex.org/W108825175","https://openalex.org/W170307911","https://openalex.org/W191383808","https://openalex.org/W196385585","https://openalex.org/W210592000","https://openalex.org/W995630646","https://openalex.org/W1520735736","https://openalex.org/W1534506107","https://openalex.org/W1965555277","https://openalex.org/W1990495631","https://openalex.org/W2030231640","https://openalex.org/W2063978378","https://openalex.org/W2110381504","https://openalex.org/W2111174809","https://openalex.org/W2135046866","https://openalex.org/W2494229806","https://openalex.org/W2801490189","https://openalex.org/W3120740533"],"related_works":["https://openalex.org/W2148249824","https://openalex.org/W3187368641","https://openalex.org/W2114625140","https://openalex.org/W2607006239","https://openalex.org/W2884430727","https://openalex.org/W1833443108","https://openalex.org/W2544537192","https://openalex.org/W2033907215","https://openalex.org/W1975924842","https://openalex.org/W2423290227"],"abstract_inverted_index":null,"counts_by_year":[{"year":2024,"cited_by_count":1},{"year":2021,"cited_by_count":1},{"year":2020,"cited_by_count":1}],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}
