{"id":"https://openalex.org/W2802254510","doi":"https://doi.org/10.1109/icassp.2018.8461842","title":"Discriminative Clustering with Cardinality Constraints","display_name":"Discriminative Clustering with Cardinality Constraints","publication_year":2018,"publication_date":"2018-04-01","ids":{"openalex":"https://openalex.org/W2802254510","doi":"https://doi.org/10.1109/icassp.2018.8461842","mag":"2802254510"},"language":"en","primary_location":{"id":"doi:10.1109/icassp.2018.8461842","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icassp.2018.8461842","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2018 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/A5101588169","display_name":"Anh T. Pham","orcid":"https://orcid.org/0000-0003-3898-2727"},"institutions":[{"id":"https://openalex.org/I131249849","display_name":"Oregon State University","ror":"https://ror.org/00ysfqy60","country_code":"US","type":"education","lineage":["https://openalex.org/I131249849"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Anh T. Pham","raw_affiliation_strings":["School of EECS, Oregon State University, Corvallis, OR"],"affiliations":[{"raw_affiliation_string":"School of EECS, Oregon State University, Corvallis, OR","institution_ids":["https://openalex.org/I131249849"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5008398853","display_name":"Raviv Raich","orcid":"https://orcid.org/0000-0001-9711-5709"},"institutions":[{"id":"https://openalex.org/I131249849","display_name":"Oregon State University","ror":"https://ror.org/00ysfqy60","country_code":"US","type":"education","lineage":["https://openalex.org/I131249849"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Raviv Raich","raw_affiliation_strings":["School of EECS, Oregon State University, Corvallis, OR"],"affiliations":[{"raw_affiliation_string":"School of EECS, Oregon State University, Corvallis, OR","institution_ids":["https://openalex.org/I131249849"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5064053803","display_name":"Xiaoli Z. Fern","orcid":null},"institutions":[{"id":"https://openalex.org/I131249849","display_name":"Oregon State University","ror":"https://ror.org/00ysfqy60","country_code":"US","type":"education","lineage":["https://openalex.org/I131249849"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Xiaoli Z. Fern","raw_affiliation_strings":["School of EECS, Oregon State University, Corvallis, OR"],"affiliations":[{"raw_affiliation_string":"School of EECS, Oregon State University, Corvallis, OR","institution_ids":["https://openalex.org/I131249849"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5101588169"],"corresponding_institution_ids":["https://openalex.org/I131249849"],"apc_list":null,"apc_paid":null,"fwci":0.1185,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.42550507,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":94},"biblio":{"volume":"2","issue":null,"first_page":"2291","last_page":"2295"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10057","display_name":"Face and Expression Recognition","score":0.9991999864578247,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"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/T10057","display_name":"Face and Expression Recognition","score":0.9991999864578247,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"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/T10637","display_name":"Advanced Clustering Algorithms Research","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/T11901","display_name":"Bayesian Methods and Mixture Models","score":0.9970999956130981,"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/discriminative-model","display_name":"Discriminative model","score":0.7472702860832214},{"id":"https://openalex.org/keywords/cluster-analysis","display_name":"Cluster analysis","score":0.7249311208724976},{"id":"https://openalex.org/keywords/cardinality","display_name":"Cardinality (data modeling)","score":0.713045597076416},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6849503517150879},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.38896679878234863},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.26839858293533325}],"concepts":[{"id":"https://openalex.org/C97931131","wikidata":"https://www.wikidata.org/wiki/Q5282087","display_name":"Discriminative model","level":2,"score":0.7472702860832214},{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.7249311208724976},{"id":"https://openalex.org/C87117476","wikidata":"https://www.wikidata.org/wiki/Q362383","display_name":"Cardinality (data modeling)","level":2,"score":0.713045597076416},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6849503517150879},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.38896679878234863},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.26839858293533325}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icassp.2018.8461842","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icassp.2018.8461842","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2018 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Reduced inequalities","score":0.75,"id":"https://metadata.un.org/sdg/10"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":49,"referenced_works":["https://openalex.org/W129176699","https://openalex.org/W1495157997","https://openalex.org/W1563294799","https://openalex.org/W1564684449","https://openalex.org/W1673310716","https://openalex.org/W1968876140","https://openalex.org/W2009086942","https://openalex.org/W2011430131","https://openalex.org/W2031489346","https://openalex.org/W2049633694","https://openalex.org/W2096100960","https://openalex.org/W2097482982","https://openalex.org/W2097578601","https://openalex.org/W2098986246","https://openalex.org/W2103284199","https://openalex.org/W2103788722","https://openalex.org/W2105543877","https://openalex.org/W2107887685","https://openalex.org/W2111751070","https://openalex.org/W2115245664","https://openalex.org/W2132820034","https://openalex.org/W2134089414","https://openalex.org/W2136518509","https://openalex.org/W2137917285","https://openalex.org/W2153839362","https://openalex.org/W2156483112","https://openalex.org/W2161579136","https://openalex.org/W2165874743","https://openalex.org/W2185563688","https://openalex.org/W2293363371","https://openalex.org/W2963720402","https://openalex.org/W3015438804","https://openalex.org/W4250589301","https://openalex.org/W6605259062","https://openalex.org/W6636455955","https://openalex.org/W6637131181","https://openalex.org/W6674787384","https://openalex.org/W6674907824","https://openalex.org/W6675573114","https://openalex.org/W6676180653","https://openalex.org/W6677027053","https://openalex.org/W6677040930","https://openalex.org/W6679849079","https://openalex.org/W6679854563","https://openalex.org/W6681588610","https://openalex.org/W6683377924","https://openalex.org/W6683769772","https://openalex.org/W6684578312","https://openalex.org/W6686566240"],"related_works":["https://openalex.org/W2748952813","https://openalex.org/W2965546495","https://openalex.org/W4389116644","https://openalex.org/W2153315159","https://openalex.org/W3103844505","https://openalex.org/W259157601","https://openalex.org/W4205463238","https://openalex.org/W2110523656","https://openalex.org/W1482209366","https://openalex.org/W2521627374"],"abstract_inverted_index":{"Clustering":[0],"is":[1,15,32],"widely":[2],"used":[3],"for":[4],"exploratory":[5],"data":[6,92],"analysis":[7],"in":[8,30,45,100,105],"a":[9,52,75],"variety":[10],"of":[11,81,84,96],"applications.":[12],"Traditionally":[13],"clustering":[14,31,43],"studied":[16],"as":[17,61],"an":[18],"unsupervised":[19],"task":[20],"where":[21],"no":[22],"human":[23],"inputs":[24],"are":[25],"provided.":[26],"A":[27],"recent":[28],"trend":[29],"to":[33,39,59,78],"leverage":[34],"user":[35,58],"provided":[36],"side":[37],"information":[38],"better":[40],"infer":[41],"the":[42,63,68,82,85,94,97,108],"structure":[44],"data.":[46],"In":[47],"this":[48],"paper,":[49],"we":[50],"propose":[51],"probabilistic":[53],"graphical":[54],"model":[55,72],"that":[56],"allows":[57],"provide":[60],"input":[62],"desired":[64],"cluster":[65],"sizes,":[66],"namely":[67],"cardinality":[69,103],"constraints.":[70],"Our":[71],"also":[73],"incorporates":[74],"flexible":[76],"mechanism":[77],"inject":[79],"control":[80],"crispness":[83],"clusters.":[86],"Experiments":[87],"on":[88],"synthetic":[89],"and":[90],"real":[91],"demonstrate":[93],"effectiveness":[95],"proposed":[98],"method":[99],"learning":[101],"with":[102,107],"constraints":[104],"comparison":[106],"current":[109],"state-of-the-art.":[110]},"counts_by_year":[{"year":2020,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}