{"id":"https://openalex.org/W3114559164","doi":"https://doi.org/10.1109/tpami.2020.3047489","title":"Detecting Meaningful Clusters From High-Dimensional Data: A Strongly Consistent Sparse Center-Based Clustering Approach","display_name":"Detecting Meaningful Clusters From High-Dimensional Data: A Strongly Consistent Sparse Center-Based Clustering Approach","publication_year":2020,"publication_date":"2020-12-25","ids":{"openalex":"https://openalex.org/W3114559164","doi":"https://doi.org/10.1109/tpami.2020.3047489","mag":"3114559164","pmid":"https://pubmed.ncbi.nlm.nih.gov/33360985"},"language":"en","primary_location":{"id":"doi:10.1109/tpami.2020.3047489","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tpami.2020.3047489","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/A5076850079","display_name":"Saptarshi Chakraborty","orcid":"https://orcid.org/0000-0002-3668-637X"},"institutions":[{"id":"https://openalex.org/I95457486","display_name":"University of California, Berkeley","ror":"https://ror.org/01an7q238","country_code":"US","type":"education","lineage":["https://openalex.org/I95457486"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Saptarshi Chakraborty","raw_affiliation_strings":["Department of Statistics, University of California, Berkeley, CA, USA"],"affiliations":[{"raw_affiliation_string":"Department of Statistics, University of California, Berkeley, CA, USA","institution_ids":["https://openalex.org/I95457486"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5000078546","display_name":"Swagatam Das","orcid":"https://orcid.org/0000-0001-6843-4508"},"institutions":[{"id":"https://openalex.org/I6498739","display_name":"Indian Statistical Institute","ror":"https://ror.org/00q2w1j53","country_code":"IN","type":"education","lineage":["https://openalex.org/I6498739"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Swagatam Das","raw_affiliation_strings":["Electronics and Communication Sciences Unit, Indian Statistical Institute, Kolkata, India"],"affiliations":[{"raw_affiliation_string":"Electronics and Communication Sciences Unit, Indian Statistical Institute, Kolkata, India","institution_ids":["https://openalex.org/I6498739"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5076850079"],"corresponding_institution_ids":["https://openalex.org/I95457486"],"apc_list":null,"apc_paid":null,"fwci":4.0776,"has_fulltext":false,"cited_by_count":47,"citation_normalized_percentile":{"value":0.9502445,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":97,"max":99},"biblio":{"volume":"44","issue":"6","first_page":"2894","last_page":"2908"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10637","display_name":"Advanced Clustering Algorithms Research","score":0.9991000294685364,"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":0.9991000294685364,"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":0.9968000054359436,"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":0.9959999918937683,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/cluster-analysis","display_name":"Cluster analysis","score":0.8034939765930176},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6337633728981018},{"id":"https://openalex.org/keywords/coordinate-descent","display_name":"Coordinate descent","score":0.6089611053466797},{"id":"https://openalex.org/keywords/feature-selection","display_name":"Feature selection","score":0.5352478623390198},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5270566940307617},{"id":"https://openalex.org/keywords/clustering-high-dimensional-data","display_name":"Clustering high-dimensional data","score":0.5143212080001831},{"id":"https://openalex.org/keywords/weighting","display_name":"Weighting","score":0.49112555384635925},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.4730234146118164},{"id":"https://openalex.org/keywords/context","display_name":"Context (archaeology)","score":0.46500834822654724},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4495044946670532},{"id":"https://openalex.org/keywords/heuristic","display_name":"Heuristic","score":0.4229237735271454},{"id":"https://openalex.org/keywords/lasso","display_name":"Lasso (programming language)","score":0.41866767406463623},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.41461390256881714},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.3423905074596405}],"concepts":[{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.8034939765930176},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6337633728981018},{"id":"https://openalex.org/C157553263","wikidata":"https://www.wikidata.org/wiki/Q5168004","display_name":"Coordinate descent","level":2,"score":0.6089611053466797},{"id":"https://openalex.org/C148483581","wikidata":"https://www.wikidata.org/wiki/Q446488","display_name":"Feature selection","level":2,"score":0.5352478623390198},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5270566940307617},{"id":"https://openalex.org/C184509293","wikidata":"https://www.wikidata.org/wiki/Q5136711","display_name":"Clustering high-dimensional data","level":3,"score":0.5143212080001831},{"id":"https://openalex.org/C183115368","wikidata":"https://www.wikidata.org/wiki/Q856577","display_name":"Weighting","level":2,"score":0.49112555384635925},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.4730234146118164},{"id":"https://openalex.org/C2779343474","wikidata":"https://www.wikidata.org/wiki/Q3109175","display_name":"Context (archaeology)","level":2,"score":0.46500834822654724},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4495044946670532},{"id":"https://openalex.org/C173801870","wikidata":"https://www.wikidata.org/wiki/Q201413","display_name":"Heuristic","level":2,"score":0.4229237735271454},{"id":"https://openalex.org/C37616216","wikidata":"https://www.wikidata.org/wiki/Q3218363","display_name":"Lasso (programming language)","level":2,"score":0.41866767406463623},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.41461390256881714},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.3423905074596405},{"id":"https://openalex.org/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"score":0.0},{"id":"https://openalex.org/C126838900","wikidata":"https://www.wikidata.org/wiki/Q77604","display_name":"Radiology","level":1,"score":0.0},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","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},{"id":"https://openalex.org/C136764020","wikidata":"https://www.wikidata.org/wiki/Q466","display_name":"World Wide Web","level":1,"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/C151730666","wikidata":"https://www.wikidata.org/wiki/Q7205","display_name":"Paleontology","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/tpami.2020.3047489","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tpami.2020.3047489","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:33360985","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/33360985","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":[{"display_name":"Responsible consumption and production","id":"https://metadata.un.org/sdg/12","score":0.44999998807907104}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":87,"referenced_works":["https://openalex.org/W155032588","https://openalex.org/W1480376833","https://openalex.org/W1536072320","https://openalex.org/W1540764732","https://openalex.org/W1574090720","https://openalex.org/W1672197616","https://openalex.org/W1922371930","https://openalex.org/W1952261593","https://openalex.org/W1959178355","https://openalex.org/W1989946714","https://openalex.org/W1992929897","https://openalex.org/W1993962865","https://openalex.org/W2011430131","https://openalex.org/W2017100743","https://openalex.org/W2025729801","https://openalex.org/W2044080809","https://openalex.org/W2044729876","https://openalex.org/W2047109555","https://openalex.org/W2047555270","https://openalex.org/W2048178552","https://openalex.org/W2056243712","https://openalex.org/W2060300932","https://openalex.org/W2064921494","https://openalex.org/W2071949631","https://openalex.org/W2072017174","https://openalex.org/W2080511794","https://openalex.org/W2086943813","https://openalex.org/W2088851040","https://openalex.org/W2094909687","https://openalex.org/W2097413644","https://openalex.org/W2102831150","https://openalex.org/W2103268563","https://openalex.org/W2108435369","https://openalex.org/W2109363337","https://openalex.org/W2109553965","https://openalex.org/W2120887445","https://openalex.org/W2125070513","https://openalex.org/W2128487019","https://openalex.org/W2135046866","https://openalex.org/W2147246240","https://openalex.org/W2149982386","https://openalex.org/W2150593711","https://openalex.org/W2153233077","https://openalex.org/W2162833336","https://openalex.org/W2167689714","https://openalex.org/W2170312859","https://openalex.org/W2182722412","https://openalex.org/W2188564768","https://openalex.org/W2238173180","https://openalex.org/W2425246132","https://openalex.org/W2549601578","https://openalex.org/W2594080144","https://openalex.org/W2726396617","https://openalex.org/W2761818166","https://openalex.org/W2807979777","https://openalex.org/W2886216085","https://openalex.org/W2949561674","https://openalex.org/W2962911132","https://openalex.org/W2963057992","https://openalex.org/W2963834778","https://openalex.org/W2963836110","https://openalex.org/W2963971338","https://openalex.org/W2964030120","https://openalex.org/W2964298148","https://openalex.org/W3037425903","https://openalex.org/W3102266858","https://openalex.org/W3104927725","https://openalex.org/W3120740533","https://openalex.org/W3122140352","https://openalex.org/W4244030505","https://openalex.org/W4250589301","https://openalex.org/W4254840543","https://openalex.org/W4256007725","https://openalex.org/W4289236186","https://openalex.org/W6632014118","https://openalex.org/W6668990524","https://openalex.org/W6676358527","https://openalex.org/W6678171244","https://openalex.org/W6678457460","https://openalex.org/W6678914141","https://openalex.org/W6679854563","https://openalex.org/W6680549645","https://openalex.org/W6681031197","https://openalex.org/W6684050148","https://openalex.org/W6684513754","https://openalex.org/W6727645846","https://openalex.org/W6779837440"],"related_works":["https://openalex.org/W2380784125","https://openalex.org/W1975417825","https://openalex.org/W1612029326","https://openalex.org/W1997711767","https://openalex.org/W2810025138","https://openalex.org/W3118634075","https://openalex.org/W4386543887","https://openalex.org/W2344475471","https://openalex.org/W1997840761","https://openalex.org/W2561368111"],"abstract_inverted_index":{"In":[0,65,150],"context":[1],"to":[2,17,44,57,121,145,234],"high-dimensional":[3,87,221],"clustering,":[4,222],"the":[5,15,19,29,33,36,52,59,63,90,101,117,147,154,158,166,174,202,205,211,216],"concept":[6],"of":[7,22,24,32,54,92,103,142,157,165,188,204,227],"feature":[8,46,118,123],"weighting":[9],"has":[10],"gained":[11],"considerable":[12],"importance":[13,23],"over":[14],"years":[16],"capture":[18],"relative":[20],"degrees":[21],"different":[25],"features":[26,93],"in":[27,39,125,179,225],"revealing":[28],"cluster":[30],"structure":[31],"dataset.":[34],"However,":[35],"popular":[37],"techniques":[38],"this":[40,66],"area":[41],"either":[42],"fail":[43],"perform":[45],"selection":[47,124],"or":[48],"do":[49],"not":[50,171,223],"preserve":[51],"simplicity":[53],"Lloyd's":[55,143],"heuristic":[56],"solve":[58],"k-means":[60,73,109,160,177,182],"problem":[61],"and":[62,190,193],"like.":[64],"paper,":[67],"we":[68,152,199],"propose":[69],"a":[70,79,126,132,186,195],"Lasso":[71],"Weighted":[72],"(":[74,94,105],"LW-":[75,108,159,181],"k-means)":[76],"algorithm,":[77],"as":[78,213,215],"simple":[80,133],"yet":[81],"efficient":[82],"sparse":[83,127,176],"clustering":[84,128,228],"procedure":[85],"for":[86,173,219],"data":[88],"where":[89],"number":[91,102,187],"p)":[95],"can":[96],"be":[97],"much":[98],"higher":[99],"than":[100],"observations":[104],"n).":[106],"The":[107],"method":[110,206],"imposes":[111],"an":[112,163],"l<sub>1</sub>":[113],"regularization":[114],"term":[115],"involving":[116],"weights":[119],"directly":[120],"induce":[122],"framework.":[129],"We":[130],"develop":[131],"block-coordinate":[134],"descent":[135],"type":[136],"algorithm":[137],"with":[138,232],"time-complexity":[139],"resembling":[140],"that":[141,201],"method,":[144],"optimize":[146],"proposed":[148],"objective.":[149],"addition,":[151],"establish":[153],"strong":[155],"consistency":[156],"procedure.":[161],"Such":[162],"analysis":[164],"large":[167],"sample":[168],"properties":[169],"is":[170,183,207],"available":[172],"conventional":[175],"algorithms,":[178],"general.":[180],"tested":[184],"on":[185],"synthetic":[189],"real-life":[191],"datasets":[192],"through":[194],"detailed":[196],"experimental":[197],"analysis,":[198],"find":[200],"performance":[203],"highly":[208],"competitive":[209],"against":[210],"baselines":[212],"well":[214],"state-of-the-art":[217],"procedures":[218],"center-based":[220],"only":[224],"terms":[226],"accuracy":[229],"but":[230],"also":[231],"respect":[233],"computational":[235],"time.":[236]},"counts_by_year":[{"year":2026,"cited_by_count":2},{"year":2025,"cited_by_count":8},{"year":2024,"cited_by_count":7},{"year":2023,"cited_by_count":10},{"year":2022,"cited_by_count":15},{"year":2021,"cited_by_count":5}],"updated_date":"2026-04-13T07:58:08.660418","created_date":"2025-10-10T00:00:00"}
