{"id":"https://openalex.org/W2131174347","doi":null,"title":"Fast, Exact Model Selection and Permutation Testing for \u21132-Regularized Logistic Regression.","display_name":"Fast, Exact Model Selection and Permutation Testing for \u21132-Regularized Logistic Regression.","publication_year":2012,"publication_date":"2012-01-01","ids":{"openalex":"https://openalex.org/W2131174347","mag":"2131174347","pmid":"https://pubmed.ncbi.nlm.nih.gov/24382986","pmcid":"https://www.ncbi.nlm.nih.gov/pmc/articles/3875235"},"language":"en","primary_location":{"id":"pmid:24382986","doi":null,"is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/24382986","pdf_url":null,"source":{"id":"https://openalex.org/S4306525036","display_name":"PubMed","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":"https://openalex.org/I1299303238","host_organization_name":"National Institutes of Health","host_organization_lineage":["https://openalex.org/I1299303238"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"JMLR workshop and conference proceedings","raw_type":"Journal Article"},"volume":null,"type":"conference-paper","is_traditional":true,"indexed_in":["pubmed"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://pmc.ncbi.nlm.nih.gov/articles/PMC3875235/","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5113532360","display_name":"Bryan Conroy","orcid":null,"observed_orcids":[]},"institutions":[{"id":"https://openalex.org/I78577930","display_name":"Columbia University","ror":"https://ror.org/00hj8s172","country_code":"US","type":"education","lineage":["https://openalex.org/I78577930"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Bryan Conroy","raw_affiliation_strings":["Columbia University New York, NY"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Columbia University New York, NY","institution_ids":["https://openalex.org/I78577930"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5042749874","display_name":"Paul Sajda","orcid":"https://orcid.org/0000-0002-9738-1342","observed_orcids":["https://orcid.org/0000-0002-9738-1342"]},"institutions":[{"id":"https://openalex.org/I78577930","display_name":"Columbia University","ror":"https://ror.org/00hj8s172","country_code":"US","type":"education","lineage":["https://openalex.org/I78577930"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Paul Sajda","raw_affiliation_strings":["Columbia University New York, NY"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Columbia University New York, NY","institution_ids":["https://openalex.org/I78577930"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I78577930"],"apc_list":null,"apc_paid":null,"fwci":7.513,"has_fulltext":false,"cited_by_count":25,"citation_normalized_percentile":{"value":0.97404844,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":88,"max":97},"biblio":{"volume":"22","issue":null,"first_page":"246","last_page":"254"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10136","display_name":"Statistical Methods and Inference","score":0.9961000084877014,"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"}},"topics":[{"id":"https://openalex.org/T10136","display_name":"Statistical Methods and Inference","score":0.9961000084877014,"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/T11612","display_name":"Stochastic Gradient Optimization Techniques","score":0.000699999975040555,"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/T13141","display_name":"Statistical Methods and Applications","score":0.0006000000284984708,"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/regularized-logistic-regression","display_name":"regularized logistic regression","score":0.9660000205039978},{"id":"https://openalex.org/keywords/tikhonov-regularization","display_name":"Tikhonov regularization","score":0.8399999737739563},{"id":"https://openalex.org/keywords/model-selection","display_name":"model selection","score":0.9850000143051147},{"id":"https://openalex.org/keywords/permutation-tests","display_name":"permutation tests","score":0.9860000014305115},{"id":"https://openalex.org/keywords/computational-efficiency","display_name":"computational efficiency","score":0.6340000033378601},{"id":"https://openalex.org/keywords/iterative-estimation","display_name":"iterative estimation","score":0.6710000038146973},{"id":"https://openalex.org/keywords/complexity-reduction","display_name":"complexity reduction","score":0.36899998784065247}],"concepts":[{"id":"https://openalex.org/C151956035","wikidata":"https://www.wikidata.org/wiki/Q1132755","display_name":"Logistic regression","level":2,"score":0.7673333883285522},{"id":"https://openalex.org/C61722155","wikidata":"https://www.wikidata.org/wiki/Q6667643","display_name":"Logistic model tree","level":3,"score":0.6533241271972656},{"id":"https://openalex.org/C117568660","wikidata":"https://www.wikidata.org/wiki/Q1650843","display_name":"Multinomial logistic regression","level":2,"score":0.6280848979949951},{"id":"https://openalex.org/C83546350","wikidata":"https://www.wikidata.org/wiki/Q1139051","display_name":"Regression","level":2,"score":0.49551665782928467},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.4918551445007324},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.47650089859962463},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.4684869050979614},{"id":"https://openalex.org/C152877465","wikidata":"https://www.wikidata.org/wiki/Q208042","display_name":"Regression analysis","level":2,"score":0.4355148673057556},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4351557493209839},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.43492391705513},{"id":"https://openalex.org/C81917197","wikidata":"https://www.wikidata.org/wiki/Q628760","display_name":"Selection (genetic algorithm)","level":2,"score":0.4315282702445984},{"id":"https://openalex.org/C148483581","wikidata":"https://www.wikidata.org/wiki/Q446488","display_name":"Feature selection","level":2,"score":0.41006654500961304},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4090624153614044},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.353906512260437}],"mesh":[],"locations_count":3,"locations":[{"id":"pmid:24382986","doi":null,"is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/24382986","pdf_url":null,"source":{"id":"https://openalex.org/S4306525036","display_name":"PubMed","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":"https://openalex.org/I1299303238","host_organization_name":"National Institutes of Health","host_organization_lineage":["https://openalex.org/I1299303238"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"JMLR workshop and conference proceedings","raw_type":"Journal Article"},{"id":"pmh:oai:pubmedcentral.nih.gov:3875235","doi":null,"is_oa":true,"landing_page_url":"https://pmc.ncbi.nlm.nih.gov/articles/PMC3875235/","pdf_url":null,"source":{"id":"https://openalex.org/S2764455111","display_name":"PubMed Central","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":"https://openalex.org/I1299303238","host_organization_name":"National Institutes of Health","host_organization_lineage":["https://openalex.org/I1299303238"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"acceptedVersion","is_accepted":true,"is_published":false,"raw_source_name":"JMLR Workshop Conf Proc","raw_type":"Text"},{"id":"mag:2131174347","doi":null,"is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/24382986","pdf_url":null,"source":{"id":"https://openalex.org/S4306525036","display_name":"PubMed","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":"https://openalex.org/I1299303238","host_organization_name":"National Institutes of Health","host_organization_lineage":["https://openalex.org/I1299303238"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false,"raw_source_name":"PubMed","raw_type":null}],"best_oa_location":{"id":"pmh:oai:pubmedcentral.nih.gov:3875235","doi":null,"is_oa":true,"landing_page_url":"https://pmc.ncbi.nlm.nih.gov/articles/PMC3875235/","pdf_url":null,"source":{"id":"https://openalex.org/S2764455111","display_name":"PubMed Central","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":"https://openalex.org/I1299303238","host_organization_name":"National Institutes of Health","host_organization_lineage":["https://openalex.org/I1299303238"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"acceptedVersion","is_accepted":true,"is_published":false,"raw_source_name":"JMLR Workshop Conf Proc","raw_type":"Text"},"sustainable_development_goals":[],"study_designs":[],"awards":[{"id":"https://openalex.org/G8207788638","display_name":"Multimodal Neuroimaging for Mapping Decision Making in the Human Brain","funder_award_id":"R01MH085092","funder_id":"https://openalex.org/F4320337346","funder_display_name":"National Institute of Mental Health"}],"funders":[{"id":"https://openalex.org/F4320337346","display_name":"National Institute of Mental Health","ror":"https://ror.org/04xeg9z08"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":19,"referenced_works":["https://openalex.org/W155555924","https://openalex.org/W307744830","https://openalex.org/W391578156","https://openalex.org/W1491300635","https://openalex.org/W1524688041","https://openalex.org/W1590879322","https://openalex.org/W1680392829","https://openalex.org/W1973948212","https://openalex.org/W2005245664","https://openalex.org/W2043906316","https://openalex.org/W2044421224","https://openalex.org/W2112796928","https://openalex.org/W2115549238","https://openalex.org/W2150579376","https://openalex.org/W2166183437","https://openalex.org/W2247522248","https://openalex.org/W2588081979","https://openalex.org/W2798909945","https://openalex.org/W4294541781"],"related_works":["https://openalex.org/W2788147515","https://openalex.org/W2962018611","https://openalex.org/W2164078599","https://openalex.org/W138876763","https://openalex.org/W7100795720","https://openalex.org/W2027197817","https://openalex.org/W2949498201","https://openalex.org/W7099825374","https://openalex.org/W1968624624","https://openalex.org/W7101183236"],"abstract_inverted_index":{"Regularized":[0],"logistic":[1,48,69],"regression":[2,49,70],"is":[3,51,112],"a":[4,64,107],"standard":[5],"classification":[6],"method":[7,105],"used":[8],"in":[9,29,54,62],"statistics":[10],"and":[11,31,57],"machine":[12],"learning.":[13],"Unlike":[14],"regularized":[15,47],"least":[16],"squares":[17],"problems":[18,71,81],"such":[19],"as":[20],"ridge":[21],"regression,":[22],"the":[23,43,80,94,97],"parameter":[24],"estimates":[25],"cannot":[26],"be":[27,34,73],"computed":[28],"closed-form":[30],"instead":[32],"must":[33,72],"estimated":[35],"using":[36],"an":[37,84],"iterative":[38,85],"technique.":[39],"This":[40],"paper":[41],"addresses":[42],"computational":[44,90],"problem":[45],"of":[46,67],"that":[50,103],"commonly":[52],"encountered":[53],"model":[55],"selection":[56],"classifier":[58],"statistical":[59],"significance":[60],"testing,":[61],"which":[63,87,111],"large":[65],"number":[66],"related":[68,98],"solved":[74],"for.":[75],"Our":[76],"proposed":[77],"approach":[78],"solves":[79],"simultaneously":[82],"through":[83],"technique,":[86],"also":[88],"garners":[89],"efficiencies":[91],"by":[92,115],"leveraging":[93],"redundancies":[95],"across":[96],"problems.":[99],"We":[100],"demonstrate":[101],"analytically":[102],"our":[104,116],"provides":[106],"substantial":[108],"complexity":[109],"reduction,":[110],"further":[113],"validated":[114],"results":[117],"on":[118],"real-world":[119],"datasets.":[120]},"counts_by_year":[{"year":2024,"cited_by_count":1},{"year":2021,"cited_by_count":5},{"year":2020,"cited_by_count":1},{"year":2019,"cited_by_count":3},{"year":2018,"cited_by_count":4},{"year":2016,"cited_by_count":1},{"year":2015,"cited_by_count":3},{"year":2014,"cited_by_count":2},{"year":2013,"cited_by_count":4},{"year":2012,"cited_by_count":1}],"updated_date":"2026-11-10T11:39:43.021295","created_date":"2016-06-24T00:00:00"}
