{"id":"https://openalex.org/W1477104975","doi":"https://doi.org/10.1109/tpami.2016.2522443","title":"A Model Selection Approach for Clustering a Multinomial Sequence with Non-Negative Factorization","display_name":"A Model Selection Approach for Clustering a Multinomial Sequence with Non-Negative Factorization","publication_year":2016,"publication_date":"2016-01-27","ids":{"openalex":"https://openalex.org/W1477104975","doi":"https://doi.org/10.1109/tpami.2016.2522443","mag":"1477104975","pmid":"https://pubmed.ncbi.nlm.nih.gov/27824580"},"language":"en","primary_location":{"id":"doi:10.1109/tpami.2016.2522443","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tpami.2016.2522443","pdf_url":null,"source":{"id":"https://openalex.org/S199944782","display_name":"IEEE Transactions on Pattern Analysis and Machine Intelligence","issn_l":"0162-8828","issn":["0162-8828","1939-3539","2160-9292"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320439","host_organization_name":"IEEE Computer Society","host_organization_lineage":["https://openalex.org/P4310320439","https://openalex.org/P4310319808"],"host_organization_lineage_names":["IEEE Computer Society","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 Pattern Analysis and Machine Intelligence","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","pubmed"],"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/A5046793514","display_name":"Nam H. Lee","orcid":null},"institutions":[{"id":"https://openalex.org/I145311948","display_name":"Johns Hopkins University","ror":"https://ror.org/00za53h95","country_code":"US","type":"education","lineage":["https://openalex.org/I145311948"]},{"id":"https://openalex.org/I889937125","display_name":"National Patient Safety Foundation","ror":"https://ror.org/01df6fw27","country_code":"US","type":"nonprofit","lineage":["https://openalex.org/I889937125"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Nam H. Lee","raw_affiliation_strings":["Armstrong Institute for Patient Safety and Quality, Johns Hopkins University, Baltimore, MD"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Armstrong Institute for Patient Safety and Quality, Johns Hopkins University, Baltimore, MD","institution_ids":["https://openalex.org/I889937125","https://openalex.org/I145311948"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5075421122","display_name":"Runze Tang","orcid":"https://orcid.org/0000-0003-1127-6726"},"institutions":[{"id":"https://openalex.org/I145311948","display_name":"Johns Hopkins University","ror":"https://ror.org/00za53h95","country_code":"US","type":"education","lineage":["https://openalex.org/I145311948"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Runze Tang","raw_affiliation_strings":["Department of Applied Mathematics and Statistics, Johns Hopkins University, Baltimore, MD","Department of Applied Mathematics and Statistics, Johns Hopkins University, Baltimore, Md"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Applied Mathematics and Statistics, Johns Hopkins University, Baltimore, MD","institution_ids":["https://openalex.org/I145311948"]},{"raw_affiliation_string":"Department of Applied Mathematics and Statistics, Johns Hopkins University, Baltimore, Md","institution_ids":["https://openalex.org/I145311948"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5031834098","display_name":"Carey E. Priebe","orcid":"https://orcid.org/0000-0002-0139-7201"},"institutions":[{"id":"https://openalex.org/I145311948","display_name":"Johns Hopkins University","ror":"https://ror.org/00za53h95","country_code":"US","type":"education","lineage":["https://openalex.org/I145311948"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Carey E. Priebe","raw_affiliation_strings":["Department of Applied Mathematics and Statistics, Johns Hopkins University, Baltimore, MD","Department of Applied Mathematics and Statistics, Johns Hopkins University, Baltimore, Md"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Applied Mathematics and Statistics, Johns Hopkins University, Baltimore, MD","institution_ids":["https://openalex.org/I145311948"]},{"raw_affiliation_string":"Department of Applied Mathematics and Statistics, Johns Hopkins University, Baltimore, Md","institution_ids":["https://openalex.org/I145311948"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5087489451","display_name":"Michael A. Rosen","orcid":"https://orcid.org/0000-0002-6621-906X"},"institutions":[{"id":"https://openalex.org/I145311948","display_name":"Johns Hopkins University","ror":"https://ror.org/00za53h95","country_code":"US","type":"education","lineage":["https://openalex.org/I145311948"]},{"id":"https://openalex.org/I889937125","display_name":"National Patient Safety Foundation","ror":"https://ror.org/01df6fw27","country_code":"US","type":"nonprofit","lineage":["https://openalex.org/I889937125"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Michael Rosen","raw_affiliation_strings":["Armstrong Institute for Patient Safety and Quality, Johns Hopkins University, Baltimore, MD"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Armstrong Institute for Patient Safety and Quality, Johns Hopkins University, Baltimore, MD","institution_ids":["https://openalex.org/I889937125","https://openalex.org/I145311948"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.8833,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":{"value":0.83162691,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":94},"biblio":{"volume":"38","issue":"12","first_page":"2345","last_page":"2358"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11901","display_name":"Bayesian Methods and Mixture Models","score":0.9998999834060669,"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":0.9998999834060669,"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/T10136","display_name":"Statistical Methods and Inference","score":0.9970999956130981,"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/T10243","display_name":"Statistical Methods and Bayesian Inference","score":0.9947999715805054,"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/multinomial-distribution","display_name":"Multinomial distribution","score":0.8557929396629333},{"id":"https://openalex.org/keywords/model-selection","display_name":"Model selection","score":0.6756868362426758},{"id":"https://openalex.org/keywords/cluster-analysis","display_name":"Cluster analysis","score":0.6619958877563477},{"id":"https://openalex.org/keywords/selection","display_name":"Selection (genetic algorithm)","score":0.6135101914405823},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5374940037727356},{"id":"https://openalex.org/keywords/rank","display_name":"Rank (graph theory)","score":0.5363925695419312},{"id":"https://openalex.org/keywords/sequence","display_name":"Sequence (biology)","score":0.5312380790710449},{"id":"https://openalex.org/keywords/projection","display_name":"Projection (relational algebra)","score":0.5135655403137207},{"id":"https://openalex.org/keywords/factorization","display_name":"Factorization","score":0.4601282775402069},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.452620267868042},{"id":"https://openalex.org/keywords/estimation-theory","display_name":"Estimation theory","score":0.42263054847717285},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.38409310579299927},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3832557797431946},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.37993091344833374},{"id":"https://openalex.org/keywords/mathematical-optimization","display_name":"Mathematical optimization","score":0.3478676378726959},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.2908148467540741},{"id":"https://openalex.org/keywords/combinatorics","display_name":"Combinatorics","score":0.0830453634262085}],"concepts":[{"id":"https://openalex.org/C192065140","wikidata":"https://www.wikidata.org/wiki/Q1147928","display_name":"Multinomial distribution","level":2,"score":0.8557929396629333},{"id":"https://openalex.org/C93959086","wikidata":"https://www.wikidata.org/wiki/Q6888345","display_name":"Model selection","level":2,"score":0.6756868362426758},{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.6619958877563477},{"id":"https://openalex.org/C81917197","wikidata":"https://www.wikidata.org/wiki/Q628760","display_name":"Selection (genetic algorithm)","level":2,"score":0.6135101914405823},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5374940037727356},{"id":"https://openalex.org/C164226766","wikidata":"https://www.wikidata.org/wiki/Q7293202","display_name":"Rank (graph theory)","level":2,"score":0.5363925695419312},{"id":"https://openalex.org/C2778112365","wikidata":"https://www.wikidata.org/wiki/Q3511065","display_name":"Sequence (biology)","level":2,"score":0.5312380790710449},{"id":"https://openalex.org/C57493831","wikidata":"https://www.wikidata.org/wiki/Q3134666","display_name":"Projection (relational algebra)","level":2,"score":0.5135655403137207},{"id":"https://openalex.org/C187834632","wikidata":"https://www.wikidata.org/wiki/Q188804","display_name":"Factorization","level":2,"score":0.4601282775402069},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.452620267868042},{"id":"https://openalex.org/C167928553","wikidata":"https://www.wikidata.org/wiki/Q1376021","display_name":"Estimation theory","level":2,"score":0.42263054847717285},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.38409310579299927},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3832557797431946},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.37993091344833374},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.3478676378726959},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.2908148467540741},{"id":"https://openalex.org/C114614502","wikidata":"https://www.wikidata.org/wiki/Q76592","display_name":"Combinatorics","level":1,"score":0.0830453634262085},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0},{"id":"https://openalex.org/C54355233","wikidata":"https://www.wikidata.org/wiki/Q7162","display_name":"Genetics","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/tpami.2016.2522443","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tpami.2016.2522443","pdf_url":null,"source":{"id":"https://openalex.org/S199944782","display_name":"IEEE Transactions on Pattern Analysis and Machine Intelligence","issn_l":"0162-8828","issn":["0162-8828","1939-3539","2160-9292"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320439","host_organization_name":"IEEE Computer Society","host_organization_lineage":["https://openalex.org/P4310320439","https://openalex.org/P4310319808"],"host_organization_lineage_names":["IEEE Computer Society","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 Pattern Analysis and Machine Intelligence","raw_type":"journal-article"},{"id":"pmid:27824580","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/27824580","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,"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":"IEEE transactions on pattern analysis and machine intelligence","raw_type":null}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G3990529561","display_name":null,"funder_award_id":"FA8750-12-2-0303","funder_id":"https://openalex.org/F4320338294","funder_display_name":"Air Force Research Laboratory"}],"funders":[{"id":"https://openalex.org/F4320310145","display_name":"Johns Hopkins University","ror":"https://ror.org/00za53h95"},{"id":"https://openalex.org/F4320315254","display_name":"Innovative Research Group Project of the National Natural Science Foundation of China","ror":null},{"id":"https://openalex.org/F4320332180","display_name":"Defense Advanced Research Projects Agency","ror":"https://ror.org/02caytj08"},{"id":"https://openalex.org/F4320338294","display_name":"Air Force Research Laboratory","ror":"https://ror.org/02e2egq70"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":30,"referenced_works":["https://openalex.org/W1580319542","https://openalex.org/W1795974289","https://openalex.org/W1987971958","https://openalex.org/W1996023858","https://openalex.org/W2011832962","https://openalex.org/W2013013263","https://openalex.org/W2017288758","https://openalex.org/W2033403400","https://openalex.org/W2033579242","https://openalex.org/W2076566842","https://openalex.org/W2084134149","https://openalex.org/W2105503503","https://openalex.org/W2117812871","https://openalex.org/W2136015602","https://openalex.org/W2136787567","https://openalex.org/W2140318696","https://openalex.org/W2143869282","https://openalex.org/W2149684740","https://openalex.org/W2616032753","https://openalex.org/W2951994466","https://openalex.org/W2963873688","https://openalex.org/W3017143921","https://openalex.org/W3125371518","https://openalex.org/W4244030505","https://openalex.org/W6628792816","https://openalex.org/W6634779745","https://openalex.org/W6638111265","https://openalex.org/W6675606416","https://openalex.org/W6680702173","https://openalex.org/W6680770193"],"related_works":["https://openalex.org/W2955220190","https://openalex.org/W2052791731","https://openalex.org/W2117588607","https://openalex.org/W1976212024","https://openalex.org/W2073599813","https://openalex.org/W2949363319","https://openalex.org/W4299965069","https://openalex.org/W1477104975","https://openalex.org/W2113262364","https://openalex.org/W3140006633"],"abstract_inverted_index":{"We":[0,18,113,134],"consider":[1],"a":[2,6,14,20,23,48,57,66,83],"problem":[3],"of":[4,8,13,22,59,71],"clustering":[5],"sequence":[7,58],"multinomial":[9,61,72],"observations":[10],"by":[11,117],"way":[12,49],"model":[15,28,121],"selection":[16,29,122],"criterion.":[17],"propose":[19,102],"form":[21],"penalty":[24],"term":[25],"for":[26,77],"the":[27,35,44,69],"procedure.":[30],"Our":[31],"approach":[32,116,138],"subsumes":[33],"both":[34],"conventional":[36,45],"AIC":[37],"and":[38,91,124,144],"BIC":[39],"criteria":[40,46],"but":[41],"also":[42,55,135],"extends":[43],"in":[47,108],"that":[50,119],"it":[51],"can":[52],"be":[53,75],"applicable":[54],"to":[56,87,94,103],"sparse":[60],"observations,":[62],"where":[63],"even":[64],"within":[65],"same":[67],"cluster,":[68],"number":[70],"trials":[73],"may":[74],"different":[76,78],"observations.":[79],"In":[80],"addition,":[81],"as":[82],"preliminary":[84,125],"estimation":[85,126],"step":[86,127],"maximum":[88,95],"likelihood":[89],"estimation,":[90,100],"more":[92],"generally,":[93],"L":[96],"<sub":[97],"xmlns:mml=\"http://www.w3.org/1998/Math/MathML\"":[98],"xmlns:xlink=\"http://www.w3.org/1999/xlink\">q</sub>":[99],"we":[101],"use":[104],"reduced":[105],"rank":[106],"projection":[107],"combination":[109],"with":[110],"non-negative":[111],"factorization.":[112],"motivate":[114],"our":[115,120,137],"showing":[118],"criterion":[123],"yield":[128],"consistent":[129],"estimates":[130],"under":[131],"simplifying":[132],"assumptions.":[133],"illustrate":[136],"through":[139],"numerical":[140],"experiments":[141],"using":[142],"real":[143],"simulated":[145],"data.":[146]},"counts_by_year":[{"year":2018,"cited_by_count":1},{"year":2017,"cited_by_count":1}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}