{"id":"https://openalex.org/W3160297038","doi":"https://doi.org/10.1109/icassp39728.2021.9413754","title":"Unified Clustering and Outlier Detection on Specialized Hardware","display_name":"Unified Clustering and Outlier Detection on Specialized Hardware","publication_year":2021,"publication_date":"2021-05-13","ids":{"openalex":"https://openalex.org/W3160297038","doi":"https://doi.org/10.1109/icassp39728.2021.9413754","mag":"3160297038"},"language":"en","primary_location":{"id":"doi:10.1109/icassp39728.2021.9413754","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icassp39728.2021.9413754","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ICASSP 2021 - 2021 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/A5087004754","display_name":"Eldan Cohen","orcid":"https://orcid.org/0000-0001-5767-6683"},"institutions":[{"id":"https://openalex.org/I185261750","display_name":"University of Toronto","ror":"https://ror.org/03dbr7087","country_code":"CA","type":"education","lineage":["https://openalex.org/I185261750"]}],"countries":["CA"],"is_corresponding":false,"raw_author_name":"Eldan Cohen","raw_affiliation_strings":["University of Toronto, Toronto, Canada"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Toronto, Toronto, Canada","institution_ids":["https://openalex.org/I185261750"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5090227260","display_name":"Hayato Ushijima\u2010Mwesigwa","orcid":"https://orcid.org/0000-0002-1442-3077"},"institutions":[{"id":"https://openalex.org/I4210094759","display_name":"Fujitsu (United States)","ror":"https://ror.org/0073whr05","country_code":"US","type":"company","lineage":["https://openalex.org/I2252096349","https://openalex.org/I4210094759"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Hayato Ushijima-Mwesigwa","raw_affiliation_strings":["Fujitsu Laboratories of America, Inc., Sunnyvale, CA, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Fujitsu Laboratories of America, Inc., Sunnyvale, CA, USA","institution_ids":["https://openalex.org/I4210094759"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5078826707","display_name":"Avradip Mandal","orcid":null},"institutions":[{"id":"https://openalex.org/I4210094759","display_name":"Fujitsu (United States)","ror":"https://ror.org/0073whr05","country_code":"US","type":"company","lineage":["https://openalex.org/I2252096349","https://openalex.org/I4210094759"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Avradip Mandal","raw_affiliation_strings":["Fujitsu Laboratories of America, Inc., Sunnyvale, CA, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Fujitsu Laboratories of America, Inc., Sunnyvale, CA, USA","institution_ids":["https://openalex.org/I4210094759"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100605963","display_name":"Arnab Roy","orcid":"https://orcid.org/0000-0002-3284-7076"},"institutions":[{"id":"https://openalex.org/I4210094759","display_name":"Fujitsu (United States)","ror":"https://ror.org/0073whr05","country_code":"US","type":"company","lineage":["https://openalex.org/I2252096349","https://openalex.org/I4210094759"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Arnab Roy","raw_affiliation_strings":["Fujitsu Laboratories of America, Inc., Sunnyvale, CA, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Fujitsu Laboratories of America, Inc., Sunnyvale, CA, USA","institution_ids":["https://openalex.org/I4210094759"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":4,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.1399,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.53414457,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":94},"biblio":{"volume":"2","issue":null,"first_page":"3770","last_page":"3774"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11512","display_name":"Anomaly Detection Techniques and Applications","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/T11512","display_name":"Anomaly Detection Techniques and Applications","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/T10876","display_name":"Fault Detection and Control Systems","score":0.9944999814033508,"subfield":{"id":"https://openalex.org/subfields/2207","display_name":"Control and Systems Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T12391","display_name":"Artificial Immune Systems Applications","score":0.9907000064849854,"subfield":{"id":"https://openalex.org/subfields/2204","display_name":"Biomedical Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/cluster-analysis","display_name":"Cluster analysis","score":0.8233967423439026},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7389055490493774},{"id":"https://openalex.org/keywords/anomaly-detection","display_name":"Anomaly detection","score":0.7361802458763123},{"id":"https://openalex.org/keywords/outlier","display_name":"Outlier","score":0.6333156824111938},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.4707629978656769},{"id":"https://openalex.org/keywords/quadratic-unconstrained-binary-optimization","display_name":"Quadratic unconstrained binary optimization","score":0.4265249967575073},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.40210390090942383},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.36440509557724}],"concepts":[{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.8233967423439026},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7389055490493774},{"id":"https://openalex.org/C739882","wikidata":"https://www.wikidata.org/wiki/Q3560506","display_name":"Anomaly detection","level":2,"score":0.7361802458763123},{"id":"https://openalex.org/C79337645","wikidata":"https://www.wikidata.org/wiki/Q779824","display_name":"Outlier","level":2,"score":0.6333156824111938},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.4707629978656769},{"id":"https://openalex.org/C177179195","wikidata":"https://www.wikidata.org/wiki/Q7268372","display_name":"Quadratic unconstrained binary optimization","level":4,"score":0.4265249967575073},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.40210390090942383},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.36440509557724},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0},{"id":"https://openalex.org/C84114770","wikidata":"https://www.wikidata.org/wiki/Q46344","display_name":"Quantum","level":2,"score":0.0},{"id":"https://openalex.org/C58053490","wikidata":"https://www.wikidata.org/wiki/Q176555","display_name":"Quantum computer","level":3,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icassp39728.2021.9413754","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icassp39728.2021.9413754","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ICASSP 2021 - 2021 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/9","score":0.4300000071525574,"display_name":"Industry, innovation and infrastructure"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":34,"referenced_works":["https://openalex.org/W1532325895","https://openalex.org/W1560013842","https://openalex.org/W1584412742","https://openalex.org/W2073459066","https://openalex.org/W2096100960","https://openalex.org/W2107105977","https://openalex.org/W2122646361","https://openalex.org/W2143077131","https://openalex.org/W2144182447","https://openalex.org/W2163145488","https://openalex.org/W2165874743","https://openalex.org/W2338990760","https://openalex.org/W2395916081","https://openalex.org/W2406579279","https://openalex.org/W2605029335","https://openalex.org/W2750232680","https://openalex.org/W2887230019","https://openalex.org/W2898784085","https://openalex.org/W2936863785","https://openalex.org/W2946426480","https://openalex.org/W2957202140","https://openalex.org/W2963546261","https://openalex.org/W3017491297","https://openalex.org/W3089543401","https://openalex.org/W3099247853","https://openalex.org/W3099977377","https://openalex.org/W3104869795","https://openalex.org/W3120740533","https://openalex.org/W4213009331","https://openalex.org/W4235169531","https://openalex.org/W4239954780","https://openalex.org/W6668990524","https://openalex.org/W6681368692","https://openalex.org/W6684578312"],"related_works":["https://openalex.org/W4319653966","https://openalex.org/W4224943954","https://openalex.org/W4382407643","https://openalex.org/W4286530336","https://openalex.org/W3123380476","https://openalex.org/W2499612753","https://openalex.org/W3111802945","https://openalex.org/W2946096271","https://openalex.org/W2295423552","https://openalex.org/W3107369729"],"abstract_inverted_index":{"Clustering":[0],"and":[1,26,89,93,109],"outlier":[2,27,90],"detection":[3,28,91],"are":[4],"often":[5],"studied":[6],"as":[7,55],"separate":[8],"problems.":[9],"However,":[10],"previous":[11],"work":[12],"has":[13,35,62],"shown":[14],"that":[15,34],"a":[16,30,81,99],"unified":[17,87],"approach":[18],"can":[19],"lead":[20],"to":[21,64,103],"better":[22],"performance.":[23],"Unified":[24],"clustering":[25,88],"is":[29],"hard":[31],"combinatorial":[32,52],"problem":[33,92],"received":[36],"significant":[37],"attention":[38],"in":[39,67,71],"recent":[40,43],"years.":[41],"The":[42],"emergence":[44],"of":[45,50,85,115],"specialized":[46,100],"optimization":[47],"hardware":[48],"capable":[49],"solving":[51],"problems":[53],"formulated":[54],"Quadratic":[56],"Unconstrained":[57],"Binary":[58],"Optimization":[59],"(QUBO)":[60],"models":[61],"led":[63],"increased":[65],"interest":[66],"harnessing":[68],"these":[69],"platforms":[70],"core":[72],"data":[73],"mining":[74],"tasks.":[75],"In":[76],"this":[77],"work,":[78],"we":[79],"present":[80],"novel":[82],"QUBO":[83],"formulation":[84],"the":[86,95,113],"use":[94],"Fujitsu":[96],"Digital":[97],"Annealer,":[98],"CMOS":[101],"hardware,":[102],"solve":[104],"it.":[105],"Experiments":[106],"on":[107],"synthetic":[108],"real":[110],"datasets":[111],"demonstrate":[112],"effectiveness":[114],"our":[116],"approach.":[117]},"counts_by_year":[{"year":2022,"cited_by_count":1}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}