{"id":"https://openalex.org/W2963525751","doi":"https://doi.org/10.1109/tsp.2016.2646664","title":"Detection of Cooperative Interactions in Logistic Regression Models","display_name":"Detection of Cooperative Interactions in Logistic Regression Models","publication_year":2016,"publication_date":"2016-12-30","ids":{"openalex":"https://openalex.org/W2963525751","doi":"https://doi.org/10.1109/tsp.2016.2646664","mag":"2963525751"},"language":"en","primary_location":{"id":"doi:10.1109/tsp.2016.2646664","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tsp.2016.2646664","pdf_url":null,"source":{"id":"https://openalex.org/S168680287","display_name":"IEEE Transactions on Signal Processing","issn_l":"1053-587X","issn":["1053-587X","1941-0476"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Signal Processing","raw_type":"journal-article"},"type":"article","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/A5080957110","display_name":"Li Xu","orcid":"https://orcid.org/0000-0002-2779-3595"},"institutions":[{"id":"https://openalex.org/I91045830","display_name":"Texas A&M University","ror":"https://ror.org/01f5ytq51","country_code":"US","type":"education","lineage":["https://openalex.org/I91045830"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Easton Li Xu","raw_affiliation_strings":["Department of Electrical and Computer Engineering, Texas A&M University, College Station, TX, USA"],"affiliations":[{"raw_affiliation_string":"Department of Electrical and Computer Engineering, Texas A&M University, College Station, TX, USA","institution_ids":["https://openalex.org/I91045830"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5073946580","display_name":"Xiaoning Qian","orcid":"https://orcid.org/0000-0002-4347-2476"},"institutions":[{"id":"https://openalex.org/I91045830","display_name":"Texas A&M University","ror":"https://ror.org/01f5ytq51","country_code":"US","type":"education","lineage":["https://openalex.org/I91045830"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Xiaoning Qian","raw_affiliation_strings":["Department of Electrical and Computer Engineering, Texas A&M University, College Station, TX, USA"],"affiliations":[{"raw_affiliation_string":"Department of Electrical and Computer Engineering, Texas A&M University, College Station, TX, USA","institution_ids":["https://openalex.org/I91045830"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5006265534","display_name":"Tie Liu","orcid":"https://orcid.org/0000-0002-6412-2432"},"institutions":[{"id":"https://openalex.org/I91045830","display_name":"Texas A&M University","ror":"https://ror.org/01f5ytq51","country_code":"US","type":"education","lineage":["https://openalex.org/I91045830"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Tie Liu","raw_affiliation_strings":["Department of Electrical and Computer Engineering, Texas A&M University, College Station, TX, USA"],"affiliations":[{"raw_affiliation_string":"Department of Electrical and Computer Engineering, Texas A&M University, College Station, TX, USA","institution_ids":["https://openalex.org/I91045830"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5009164482","display_name":"Shuguang Cui","orcid":"https://orcid.org/0000-0003-2608-775X"},"institutions":[{"id":"https://openalex.org/I84218800","display_name":"University of California, Davis","ror":"https://ror.org/05rrcem69","country_code":"US","type":"education","lineage":["https://openalex.org/I84218800"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Shuguang Cui","raw_affiliation_strings":["Department of Electrical and Computer Engineering, University of California, Davis, CA, USA"],"affiliations":[{"raw_affiliation_string":"Department of Electrical and Computer Engineering, University of California, Davis, CA, USA","institution_ids":["https://openalex.org/I84218800"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5080957110"],"corresponding_institution_ids":["https://openalex.org/I91045830"],"apc_list":null,"apc_paid":null,"fwci":0.3548,"has_fulltext":false,"cited_by_count":3,"citation_normalized_percentile":{"value":0.7195519,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":96},"biblio":{"volume":"65","issue":"7","first_page":"1765","last_page":"1780"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10136","display_name":"Statistical Methods and Inference","score":0.995199978351593,"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":0.995199978351593,"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/T10885","display_name":"Gene expression and cancer classification","score":0.9793999791145325,"subfield":{"id":"https://openalex.org/subfields/1312","display_name":"Molecular Biology"},"field":{"id":"https://openalex.org/fields/13","display_name":"Biochemistry, Genetics and Molecular Biology"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}},{"id":"https://openalex.org/T11303","display_name":"Bayesian Modeling and Causal Inference","score":0.9742000102996826,"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/pairwise-comparison","display_name":"Pairwise comparison","score":0.8227806091308594},{"id":"https://openalex.org/keywords/covariate","display_name":"Covariate","score":0.7524414658546448},{"id":"https://openalex.org/keywords/feature-selection","display_name":"Feature selection","score":0.584356427192688},{"id":"https://openalex.org/keywords/logistic-regression","display_name":"Logistic regression","score":0.5312691926956177},{"id":"https://openalex.org/keywords/outcome","display_name":"Outcome (game theory)","score":0.510087788105011},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.5095053315162659},{"id":"https://openalex.org/keywords/directed-acyclic-graph","display_name":"Directed acyclic graph","score":0.5023453235626221},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.4848674237728119},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.41967326402664185},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.3539474904537201},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.3236224055290222},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.25359031558036804},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.23298707604408264}],"concepts":[{"id":"https://openalex.org/C184898388","wikidata":"https://www.wikidata.org/wiki/Q1435712","display_name":"Pairwise comparison","level":2,"score":0.8227806091308594},{"id":"https://openalex.org/C119043178","wikidata":"https://www.wikidata.org/wiki/Q320723","display_name":"Covariate","level":2,"score":0.7524414658546448},{"id":"https://openalex.org/C148483581","wikidata":"https://www.wikidata.org/wiki/Q446488","display_name":"Feature selection","level":2,"score":0.584356427192688},{"id":"https://openalex.org/C151956035","wikidata":"https://www.wikidata.org/wiki/Q1132755","display_name":"Logistic regression","level":2,"score":0.5312691926956177},{"id":"https://openalex.org/C148220186","wikidata":"https://www.wikidata.org/wiki/Q7111912","display_name":"Outcome (game theory)","level":2,"score":0.510087788105011},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.5095053315162659},{"id":"https://openalex.org/C74197172","wikidata":"https://www.wikidata.org/wiki/Q1195339","display_name":"Directed acyclic graph","level":2,"score":0.5023453235626221},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.4848674237728119},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.41967326402664185},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.3539474904537201},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3236224055290222},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.25359031558036804},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.23298707604408264},{"id":"https://openalex.org/C144237770","wikidata":"https://www.wikidata.org/wiki/Q747534","display_name":"Mathematical economics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tsp.2016.2646664","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tsp.2016.2646664","pdf_url":null,"source":{"id":"https://openalex.org/S168680287","display_name":"IEEE Transactions on Signal Processing","issn_l":"1053-587X","issn":["1053-587X","1941-0476"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Signal Processing","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G169708629","display_name":null,"funder_award_id":"61328102","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G2245627796","display_name":null,"funder_award_id":"DMS-1622433","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"},{"id":"https://openalex.org/G2878590505","display_name":null,"funder_award_id":"CNS-1343155","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"},{"id":"https://openalex.org/G4039508203","display_name":null,"funder_award_id":"HDTRA1-13-1-0029","funder_id":"https://openalex.org/F4320306078","funder_display_name":"U.S. Department of Defense"},{"id":"https://openalex.org/G4066064560","display_name":null,"funder_award_id":"IOS-1547557","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"},{"id":"https://openalex.org/G4740607499","display_name":null,"funder_award_id":"AST-1547436","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"},{"id":"https://openalex.org/G4740692575","display_name":null,"funder_award_id":"ECCS-1305979","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"},{"id":"https://openalex.org/G5894024576","display_name":null,"funder_award_id":"ECCS-1508051","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"},{"id":"https://openalex.org/G7527124865","display_name":null,"funder_award_id":"CCF-1447235","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"}],"funders":[{"id":"https://openalex.org/F4320306076","display_name":"National Science Foundation","ror":"https://ror.org/021nxhr62"},{"id":"https://openalex.org/F4320306078","display_name":"U.S. Department of Defense","ror":"https://ror.org/0447fe631"},{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":22,"referenced_works":["https://openalex.org/W1585881990","https://openalex.org/W1963760691","https://openalex.org/W1966360257","https://openalex.org/W1969880349","https://openalex.org/W2084017738","https://openalex.org/W2100850281","https://openalex.org/W2101095383","https://openalex.org/W2101985079","https://openalex.org/W2103012681","https://openalex.org/W2114771311","https://openalex.org/W2119387367","https://openalex.org/W2138145347","https://openalex.org/W2139319528","https://openalex.org/W2154053567","https://openalex.org/W2158620919","https://openalex.org/W2171236873","https://openalex.org/W2171800571","https://openalex.org/W2478708596","https://openalex.org/W4214704140","https://openalex.org/W4233413206","https://openalex.org/W6642580820","https://openalex.org/W6680599301"],"related_works":["https://openalex.org/W2985746494","https://openalex.org/W4206042385","https://openalex.org/W2511384863","https://openalex.org/W2096089271","https://openalex.org/W2923628599","https://openalex.org/W2014100433","https://openalex.org/W2051519658","https://openalex.org/W2994787386","https://openalex.org/W2002304499","https://openalex.org/W128985311"],"abstract_inverted_index":{"An":[0],"important":[1],"problem":[2],"in":[3],"the":[4,38,41,51,61,64,84,88,92,95,98,125,129,148,155,158,167,178],"field":[5],"of":[6,32,40,60,83,87,128,154,180],"bioinformatics":[7],"is":[8,35,48,78,102,108,115],"to":[9,49,104,124,166],"identify":[10],"interactive":[11],"effects":[12,86,173],"among":[13,29],"profiled":[14],"variables":[15],"for":[16,146],"outcome":[17],"prediction.":[18],"In":[19],"this":[20],"paper,":[21],"a":[22,30,44,69,73,81,111,118],"logistic":[23],"regression":[24],"model":[25,168],"with":[26,122],"pairwise":[27,175],"interactions":[28,42,176],"set":[31],"binary":[33],"covariates":[34,62,156],"considered.":[36],"Modeling":[37],"structure":[39],"by":[43],"graph,":[45],"our":[46],"goal":[47],"recover":[50],"interaction":[52,89,100,149],"graph":[53,101,150],"from":[54,151],"independently":[55],"identically":[56],"distributed":[57],"(i.i.d.)":[58],"samples":[59,153],"and":[63,157,174],"outcome.":[65,93,159],"When":[66],"viewed":[67],"as":[68,80],"feature":[70,143],"selection":[71,144],"problem,":[72],"simple":[74,112],"quantity":[75],"called":[76],"influence":[77],"proposed":[79],"measure":[82],"marginal":[85],"terms":[90],"on":[91,117],"For":[94],"case":[96],"when":[97],"underlying":[99],"known":[103],"be":[105,164],"acyclic,":[106],"it":[107],"shown":[109],"that":[110,114,169],"algorithm":[113],"based":[116],"maximum-weight":[119],"spanning":[120],"tree":[121],"respect":[123],"plug-in":[126],"estimates":[127],"influences":[130],"not":[131],"only":[132],"has":[133],"strong":[134],"theoretical":[135],"performance":[136],"guarantees,":[137],"but":[138],"can":[139,162],"also":[140,163],"outperform":[141],"generic":[142],"algorithms":[145],"recovering":[147],"i.i.d.":[152],"Our":[160],"results":[161],"extended":[165],"includes":[170],"both":[171],"individual":[172],"via":[177],"help":[179],"an":[181],"auxiliary":[182],"covariate.":[183]},"counts_by_year":[{"year":2023,"cited_by_count":2},{"year":2018,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
