{"id":"https://openalex.org/W2916179757","doi":"https://doi.org/10.1109/icassp.2019.8682529","title":"Feature Selection for Mutlti-labeled Variables via Dependency Maximization","display_name":"Feature Selection for Mutlti-labeled Variables via Dependency Maximization","publication_year":2019,"publication_date":"2019-04-17","ids":{"openalex":"https://openalex.org/W2916179757","doi":"https://doi.org/10.1109/icassp.2019.8682529","mag":"2916179757"},"language":"en","primary_location":{"id":"doi:10.1109/icassp.2019.8682529","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icassp.2019.8682529","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ICASSP 2019 - 2019 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)","raw_type":"proceedings-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/A5081523775","display_name":"Salimeh Yasaei Sekeh","orcid":"https://orcid.org/0000-0002-0854-5422"},"institutions":[{"id":"https://openalex.org/I27837315","display_name":"University of Michigan\u2013Ann Arbor","ror":"https://ror.org/00jmfr291","country_code":"US","type":"education","lineage":["https://openalex.org/I27837315"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Salimeh Yasaei Sekeh","raw_affiliation_strings":["Department of Electrical Engineering and Computer Science, University of Michigan, Ann Arbor, MI, USA"],"affiliations":[{"raw_affiliation_string":"Department of Electrical Engineering and Computer Science, University of Michigan, Ann Arbor, MI, USA","institution_ids":["https://openalex.org/I27837315"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5077692655","display_name":"Alfred O. Hero","orcid":"https://orcid.org/0000-0002-2531-9670"},"institutions":[{"id":"https://openalex.org/I27837315","display_name":"University of Michigan\u2013Ann Arbor","ror":"https://ror.org/00jmfr291","country_code":"US","type":"education","lineage":["https://openalex.org/I27837315"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Alfred O. Hero","raw_affiliation_strings":["Department of Electrical Engineering and Computer Science, University of Michigan, Ann Arbor, MI, USA"],"affiliations":[{"raw_affiliation_string":"Department of Electrical Engineering and Computer Science, University of Michigan, Ann Arbor, MI, USA","institution_ids":["https://openalex.org/I27837315"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5081523775"],"corresponding_institution_ids":["https://openalex.org/I27837315"],"apc_list":null,"apc_paid":null,"fwci":1.1706,"has_fulltext":false,"cited_by_count":7,"citation_normalized_percentile":{"value":0.79400484,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":96},"biblio":{"volume":"3","issue":null,"first_page":"3127","last_page":"3131"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11871","display_name":"Advanced Statistical Methods and Models","score":0.9954000115394592,"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/T11871","display_name":"Advanced Statistical Methods and Models","score":0.9954000115394592,"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/T11303","display_name":"Bayesian Modeling and Causal Inference","score":0.9894999861717224,"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/T10538","display_name":"Data Mining Algorithms and Applications","score":0.983299970626831,"subfield":{"id":"https://openalex.org/subfields/1710","display_name":"Information Systems"},"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/feature-selection","display_name":"Feature selection","score":0.8197813630104065},{"id":"https://openalex.org/keywords/mutual-information","display_name":"Mutual information","score":0.6447300910949707},{"id":"https://openalex.org/keywords/mnist-database","display_name":"MNIST database","score":0.6446625590324402},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6192084550857544},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.6130064725875854},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5667146444320679},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.48356863856315613},{"id":"https://openalex.org/keywords/curse-of-dimensionality","display_name":"Curse of dimensionality","score":0.4637018144130707},{"id":"https://openalex.org/keywords/measure","display_name":"Measure (data warehouse)","score":0.4423591196537018},{"id":"https://openalex.org/keywords/dimensionality-reduction","display_name":"Dimensionality reduction","score":0.41958433389663696},{"id":"https://openalex.org/keywords/dependency","display_name":"Dependency (UML)","score":0.41074037551879883},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.38630980253219604},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.10157439112663269}],"concepts":[{"id":"https://openalex.org/C148483581","wikidata":"https://www.wikidata.org/wiki/Q446488","display_name":"Feature selection","level":2,"score":0.8197813630104065},{"id":"https://openalex.org/C152139883","wikidata":"https://www.wikidata.org/wiki/Q252973","display_name":"Mutual information","level":2,"score":0.6447300910949707},{"id":"https://openalex.org/C190502265","wikidata":"https://www.wikidata.org/wiki/Q17069496","display_name":"MNIST database","level":3,"score":0.6446625590324402},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6192084550857544},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.6130064725875854},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5667146444320679},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.48356863856315613},{"id":"https://openalex.org/C111030470","wikidata":"https://www.wikidata.org/wiki/Q1430460","display_name":"Curse of dimensionality","level":2,"score":0.4637018144130707},{"id":"https://openalex.org/C2780009758","wikidata":"https://www.wikidata.org/wiki/Q6804172","display_name":"Measure (data warehouse)","level":2,"score":0.4423591196537018},{"id":"https://openalex.org/C70518039","wikidata":"https://www.wikidata.org/wiki/Q16000077","display_name":"Dimensionality reduction","level":2,"score":0.41958433389663696},{"id":"https://openalex.org/C19768560","wikidata":"https://www.wikidata.org/wiki/Q320727","display_name":"Dependency (UML)","level":2,"score":0.41074037551879883},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.38630980253219604},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.10157439112663269},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icassp.2019.8682529","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icassp.2019.8682529","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ICASSP 2019 - 2019 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":36,"referenced_works":["https://openalex.org/W8815205","https://openalex.org/W1489238841","https://openalex.org/W1587362683","https://openalex.org/W1624804034","https://openalex.org/W1976687792","https://openalex.org/W2014068360","https://openalex.org/W2015610066","https://openalex.org/W2017337590","https://openalex.org/W2025890108","https://openalex.org/W2027390033","https://openalex.org/W2068276287","https://openalex.org/W2092939357","https://openalex.org/W2099111195","https://openalex.org/W2115729631","https://openalex.org/W2118561568","https://openalex.org/W2129000925","https://openalex.org/W2149772057","https://openalex.org/W2155344811","https://openalex.org/W2218423201","https://openalex.org/W2519513981","https://openalex.org/W2585429527","https://openalex.org/W2915025989","https://openalex.org/W2962779416","https://openalex.org/W2998216295","https://openalex.org/W3101158363","https://openalex.org/W3101241128","https://openalex.org/W3105524694","https://openalex.org/W4230367971","https://openalex.org/W4251163770","https://openalex.org/W4285719527","https://openalex.org/W6677079992","https://openalex.org/W6683024897","https://openalex.org/W6748131300","https://openalex.org/W6781870204","https://openalex.org/W6785272721","https://openalex.org/W7066667914"],"related_works":["https://openalex.org/W3137091086","https://openalex.org/W1995622179","https://openalex.org/W4391160746","https://openalex.org/W1484111231","https://openalex.org/W1552543208","https://openalex.org/W2074396517","https://openalex.org/W2166963679","https://openalex.org/W2187269125","https://openalex.org/W1641615907","https://openalex.org/W2985680200"],"abstract_inverted_index":{"Feature":[0],"selection":[1,25,78,115,124],"and":[2,72],"reducing":[3],"the":[4,35,41,61,91,109,121,129],"dimensionality":[5],"of":[6,39,63,76,89,111],"data":[7,13,131],"is":[8,27,126],"an":[9,70],"essential":[10],"step":[11],"in":[12,69],"analysis.":[14],"In":[15,119],"this":[16],"work":[17],"we":[18,50],"propose":[19],"a":[20,86,101],"new":[21],"criterion":[22,54],"for":[23,60],"feature":[24,77,114,123],"that":[26],"formulated":[28],"as":[29,79],"conditional":[30],"information":[31,44],"between":[32],"features":[33,59],"given":[34],"labeled":[36],"variable.":[37],"Instead":[38],"using":[40,85],"standard":[42],"mutual":[43],"measure":[45,88],"based":[46],"on":[47],"Kullback-Leibler":[48],"divergence,":[49],"use":[51],"our":[52,112],"proposed":[53,113,122],"to":[55,128],"filter":[56],"out":[57],"redundant":[58],"purpose":[62],"multiclass":[64],"classification.":[65],"This":[66],"approach":[67,116],"results":[68],"efficient":[71],"fast":[73],"non-parametric":[74],"implementation":[75],"it":[80],"can":[81],"be":[82],"directly":[83],"estimated":[84],"geometric":[87],"dependency,":[90],"global":[92,102],"Friedman-Rafsky":[93],"(\u0393R)":[94],"multivariate":[95],"run":[96],"test":[97],"statistic":[98],"constructed":[99],"by":[100],"minimal":[103],"spanning":[104],"tree":[105],"(MST).":[106],"We":[107],"demonstrate":[108],"advantages":[110],"through":[117],"simulation.":[118],"addition":[120],"method":[125],"applied":[127],"MNIST":[130],"set.":[132]},"counts_by_year":[{"year":2023,"cited_by_count":2},{"year":2022,"cited_by_count":1},{"year":2021,"cited_by_count":2},{"year":2020,"cited_by_count":1},{"year":2019,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
