{"id":"https://openalex.org/W3160252920","doi":"https://doi.org/10.1109/icassp39728.2021.9414687","title":"t-k-means: A ROBUST AND STABLE k-means VARIANT","display_name":"t-k-means: A ROBUST AND STABLE k-means VARIANT","publication_year":2021,"publication_date":"2021-05-13","ids":{"openalex":"https://openalex.org/W3160252920","doi":"https://doi.org/10.1109/icassp39728.2021.9414687","mag":"3160252920"},"language":"en","primary_location":{"id":"doi:10.1109/icassp39728.2021.9414687","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icassp39728.2021.9414687","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/A5100346332","display_name":"Yiming Li","orcid":"https://orcid.org/0000-0002-2258-265X"},"institutions":[{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Yiming Li","raw_affiliation_strings":["Tsinghua Shenzhen International Graduate School, Tsinghua University, China"],"affiliations":[{"raw_affiliation_string":"Tsinghua Shenzhen International Graduate School, Tsinghua University, China","institution_ids":["https://openalex.org/I99065089"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100354773","display_name":"Yang Zhang","orcid":"https://orcid.org/0000-0003-1684-6273"},"institutions":[{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yang Zhang","raw_affiliation_strings":["Tsinghua Shenzhen International Graduate School, Tsinghua University, China"],"affiliations":[{"raw_affiliation_string":"Tsinghua Shenzhen International Graduate School, Tsinghua University, China","institution_ids":["https://openalex.org/I99065089"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5059534557","display_name":"Qingtao Tang","orcid":null},"institutions":[{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Qingtao Tang","raw_affiliation_strings":["Tsinghua Shenzhen International Graduate School, Tsinghua University, China"],"affiliations":[{"raw_affiliation_string":"Tsinghua Shenzhen International Graduate School, Tsinghua University, China","institution_ids":["https://openalex.org/I99065089"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5078160191","display_name":"W\u011bip\u00e9ng Hu\u00e1ng","orcid":"https://orcid.org/0000-0003-4620-6912"},"institutions":[{"id":"https://openalex.org/I100930933","display_name":"University College Dublin","ror":"https://ror.org/05m7pjf47","country_code":"IE","type":"education","lineage":["https://openalex.org/I100930933"]}],"countries":["IE"],"is_corresponding":false,"raw_author_name":"Weipeng Huang","raw_affiliation_strings":["Insight Centre for Data Analytics, University College Dublin, Ireland"],"affiliations":[{"raw_affiliation_string":"Insight Centre for Data Analytics, University College Dublin, Ireland","institution_ids":["https://openalex.org/I100930933"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101626204","display_name":"Yong Jiang","orcid":"https://orcid.org/0000-0002-4260-1395"},"institutions":[{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]},{"id":"https://openalex.org/I4210136793","display_name":"Peng Cheng Laboratory","ror":"https://ror.org/03qdqbt06","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4210136793"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yong Jiang","raw_affiliation_strings":["PCL Research Center of Networks and Communications, Peng Cheng Laboratory, China","Tsinghua Shenzhen International Graduate School, Tsinghua University, China"],"affiliations":[{"raw_affiliation_string":"PCL Research Center of Networks and Communications, Peng Cheng Laboratory, China","institution_ids":["https://openalex.org/I4210136793"]},{"raw_affiliation_string":"Tsinghua Shenzhen International Graduate School, Tsinghua University, China","institution_ids":["https://openalex.org/I99065089"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5034104790","display_name":"Shu\u2010Tao Xia","orcid":"https://orcid.org/0000-0002-8639-982X"},"institutions":[{"id":"https://openalex.org/I4210136793","display_name":"Peng Cheng Laboratory","ror":"https://ror.org/03qdqbt06","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4210136793"]},{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Shu-Tao Xia","raw_affiliation_strings":["PCL Research Center of Networks and Communications, Peng Cheng Laboratory, China","Tsinghua Shenzhen International Graduate School, Tsinghua University, China"],"affiliations":[{"raw_affiliation_string":"PCL Research Center of Networks and Communications, Peng Cheng Laboratory, China","institution_ids":["https://openalex.org/I4210136793"]},{"raw_affiliation_string":"Tsinghua Shenzhen International Graduate School, Tsinghua University, China","institution_ids":["https://openalex.org/I99065089"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":6,"corresponding_author_ids":["https://openalex.org/A5100346332"],"corresponding_institution_ids":["https://openalex.org/I99065089"],"apc_list":null,"apc_paid":null,"fwci":1.9036,"has_fulltext":false,"cited_by_count":19,"citation_normalized_percentile":{"value":0.88113443,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":98},"biblio":{"volume":null,"issue":null,"first_page":"3120","last_page":"3124"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10637","display_name":"Advanced Clustering Algorithms Research","score":0.9977999925613403,"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/T10637","display_name":"Advanced Clustering Algorithms Research","score":0.9977999925613403,"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/T10057","display_name":"Face and Expression Recognition","score":0.9927999973297119,"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/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.9926999807357788,"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/outlier","display_name":"Outlier","score":0.7593719959259033},{"id":"https://openalex.org/keywords/robustness","display_name":"Robustness (evolution)","score":0.7377567887306213},{"id":"https://openalex.org/keywords/cluster-analysis","display_name":"Cluster analysis","score":0.7032464146614075},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.6019718050956726},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5927478671073914},{"id":"https://openalex.org/keywords/stability","display_name":"Stability (learning theory)","score":0.5626102089881897},{"id":"https://openalex.org/keywords/gaussian","display_name":"Gaussian","score":0.537447988986969},{"id":"https://openalex.org/keywords/property","display_name":"Property (philosophy)","score":0.4880343973636627},{"id":"https://openalex.org/keywords/code","display_name":"Code (set theory)","score":0.44295793771743774},{"id":"https://openalex.org/keywords/k-means-clustering","display_name":"k-means clustering","score":0.43377017974853516},{"id":"https://openalex.org/keywords/variance","display_name":"Variance (accounting)","score":0.41771817207336426},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.20146211981773376},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.09686893224716187},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.08022406697273254}],"concepts":[{"id":"https://openalex.org/C79337645","wikidata":"https://www.wikidata.org/wiki/Q779824","display_name":"Outlier","level":2,"score":0.7593719959259033},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.7377567887306213},{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.7032464146614075},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.6019718050956726},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5927478671073914},{"id":"https://openalex.org/C112972136","wikidata":"https://www.wikidata.org/wiki/Q7595718","display_name":"Stability (learning theory)","level":2,"score":0.5626102089881897},{"id":"https://openalex.org/C163716315","wikidata":"https://www.wikidata.org/wiki/Q901177","display_name":"Gaussian","level":2,"score":0.537447988986969},{"id":"https://openalex.org/C189950617","wikidata":"https://www.wikidata.org/wiki/Q937228","display_name":"Property (philosophy)","level":2,"score":0.4880343973636627},{"id":"https://openalex.org/C2776760102","wikidata":"https://www.wikidata.org/wiki/Q5139990","display_name":"Code (set theory)","level":3,"score":0.44295793771743774},{"id":"https://openalex.org/C207968372","wikidata":"https://www.wikidata.org/wiki/Q310401","display_name":"k-means clustering","level":3,"score":0.43377017974853516},{"id":"https://openalex.org/C196083921","wikidata":"https://www.wikidata.org/wiki/Q7915758","display_name":"Variance (accounting)","level":2,"score":0.41771817207336426},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.20146211981773376},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.09686893224716187},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.08022406697273254},{"id":"https://openalex.org/C111472728","wikidata":"https://www.wikidata.org/wiki/Q9471","display_name":"Epistemology","level":1,"score":0.0},{"id":"https://openalex.org/C55493867","wikidata":"https://www.wikidata.org/wiki/Q7094","display_name":"Biochemistry","level":1,"score":0.0},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0},{"id":"https://openalex.org/C121955636","wikidata":"https://www.wikidata.org/wiki/Q4116214","display_name":"Accounting","level":1,"score":0.0},{"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/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C104317684","wikidata":"https://www.wikidata.org/wiki/Q7187","display_name":"Gene","level":2,"score":0.0},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C144133560","wikidata":"https://www.wikidata.org/wiki/Q4830453","display_name":"Business","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icassp39728.2021.9414687","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icassp39728.2021.9414687","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":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320306076","display_name":"National Science Foundation","ror":"https://ror.org/021nxhr62"},{"id":"https://openalex.org/F4320320847","display_name":"Science Foundation Ireland","ror":"https://ror.org/0271asj38"},{"id":"https://openalex.org/F4320338464","display_name":"Natural Science Foundation of Zhejiang Province","ror":"https://ror.org/01h0zpd94"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":31,"referenced_works":["https://openalex.org/W87092222","https://openalex.org/W1486632395","https://openalex.org/W1555244713","https://openalex.org/W1977541023","https://openalex.org/W1992402718","https://openalex.org/W2009086942","https://openalex.org/W2064029323","https://openalex.org/W2073459066","https://openalex.org/W2109014721","https://openalex.org/W2110294373","https://openalex.org/W2137971377","https://openalex.org/W2150593711","https://openalex.org/W2166999932","https://openalex.org/W2395916081","https://openalex.org/W2406810007","https://openalex.org/W2482589566","https://openalex.org/W2532189199","https://openalex.org/W2779692282","https://openalex.org/W2802533528","https://openalex.org/W2809034148","https://openalex.org/W2884586244","https://openalex.org/W2907783748","https://openalex.org/W2989855712","https://openalex.org/W3120740533","https://openalex.org/W4235169531","https://openalex.org/W4300223101","https://openalex.org/W6628849183","https://openalex.org/W6648237178","https://openalex.org/W6668990524","https://openalex.org/W6676431381","https://openalex.org/W6770128591"],"related_works":["https://openalex.org/W3006513224","https://openalex.org/W2046456988","https://openalex.org/W2357409937","https://openalex.org/W2510582230","https://openalex.org/W2978674666","https://openalex.org/W2074430941","https://openalex.org/W2113096305","https://openalex.org/W1977636359","https://openalex.org/W2772305933","https://openalex.org/W2580722822"],"abstract_inverted_index":{"k-means":[0,30,47,74],"algorithm":[1,31,48],"is":[2,136],"one":[3],"of":[4,26,103,110,126],"the":[5,23,27,38,77,92,101,104,108,111,122,127],"most":[6],"classical":[7],"clustering":[8,112],"methods,":[9],"which":[10,61,120],"has":[11,50],"been":[12],"widely":[13],"and":[14,72,94,98,107,124],"successfully":[15],"used":[16],"in":[17],"signal":[18],"processing.":[19],"However,":[20],"due":[21],"to":[22,85],"thin-tailed":[24],"property":[25],"Gaussian":[28],"distribution,":[29],"suffers":[32],"from":[33,100],"relatively":[34,51],"poor":[35],"performance":[36],"on":[37],"dataset":[39],"containing":[40],"heavy-tailed":[41],"data":[42],"or":[43],"outliers.":[44],"Besides,":[45],"standard":[46],"also":[49,118],"weak":[52],"stability,":[53],"i.e.":[54],"its":[55,63,82,96],"results":[56,135],"have":[57],"a":[58,70],"large":[59],"variance,":[60],"reduces":[62],"credibility.":[64],"In":[65],"this":[66],"paper,":[67],"we":[68,90],"propose":[69],"robust":[71],"stable":[73],"variant,":[75],"dubbed":[76],"t-k-means,":[78],"as":[79,81],"well":[80],"fast":[83],"version":[84],"alleviate":[86],"those":[87],"problems.":[88],"Theoretically,":[89],"derive":[91],"t-k-means":[93],"analyze":[95],"robustness":[97],"stability":[99],"aspect":[102],"loss":[105],"function":[106],"expression":[109],"center,":[113],"respectively.":[114],"Extensive":[115],"experiments":[116],"are":[117],"conducted,":[119],"verify":[121],"effectiveness":[123],"efficiency":[125],"proposed":[128],"method.":[129],"The":[130],"code":[131],"for":[132],"reproducing":[133],"main":[134],"available":[137],"at":[138],"https://github.com/THUYimingLi/t-k-means.":[139]},"counts_by_year":[{"year":2025,"cited_by_count":5},{"year":2024,"cited_by_count":3},{"year":2023,"cited_by_count":4},{"year":2022,"cited_by_count":6},{"year":2021,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}