{"id":"https://openalex.org/W2025683492","doi":"https://doi.org/10.1145/1014052.1014115","title":"Parallel computation of high dimensional robust correlation and covariance matrices","display_name":"Parallel computation of high dimensional robust correlation and covariance matrices","publication_year":2004,"publication_date":"2004-08-22","ids":{"openalex":"https://openalex.org/W2025683492","doi":"https://doi.org/10.1145/1014052.1014115","mag":"2025683492"},"language":"en","primary_location":{"id":"doi:10.1145/1014052.1014115","is_oa":false,"landing_page_url":"https://doi.org/10.1145/1014052.1014115","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the tenth ACM SIGKDD international conference on Knowledge discovery and data mining","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/A5004835200","display_name":"James Chilson","orcid":null},"institutions":[{"id":"https://openalex.org/I141945490","display_name":"University of British Columbia","ror":"https://ror.org/03rmrcq20","country_code":"CA","type":"education","lineage":["https://openalex.org/I141945490"]}],"countries":["CA"],"is_corresponding":true,"raw_author_name":"James Chilson","raw_affiliation_strings":["University of British Columbia, Vancouver, BC, Canada"],"affiliations":[{"raw_affiliation_string":"University of British Columbia, Vancouver, BC, Canada","institution_ids":["https://openalex.org/I141945490"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5113567130","display_name":"Raymond T. Ng","orcid":"https://orcid.org/0000-0003-3692-8524"},"institutions":[{"id":"https://openalex.org/I141945490","display_name":"University of British Columbia","ror":"https://ror.org/03rmrcq20","country_code":"CA","type":"education","lineage":["https://openalex.org/I141945490"]}],"countries":["CA"],"is_corresponding":false,"raw_author_name":"Raymond Ng","raw_affiliation_strings":["University of British Columbia, Vancouver, BC, Canada"],"affiliations":[{"raw_affiliation_string":"University of British Columbia, Vancouver, BC, Canada","institution_ids":["https://openalex.org/I141945490"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5110147162","display_name":"Alan Wagner","orcid":null},"institutions":[{"id":"https://openalex.org/I141945490","display_name":"University of British Columbia","ror":"https://ror.org/03rmrcq20","country_code":"CA","type":"education","lineage":["https://openalex.org/I141945490"]}],"countries":["CA"],"is_corresponding":false,"raw_author_name":"Alan Wagner","raw_affiliation_strings":["University of British Columbia, Vancouver, BC, Canada"],"affiliations":[{"raw_affiliation_string":"University of British Columbia, Vancouver, BC, Canada","institution_ids":["https://openalex.org/I141945490"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5108599652","display_name":"Ruben H. Zamar","orcid":null},"institutions":[{"id":"https://openalex.org/I141945490","display_name":"University of British Columbia","ror":"https://ror.org/03rmrcq20","country_code":"CA","type":"education","lineage":["https://openalex.org/I141945490"]}],"countries":["CA"],"is_corresponding":false,"raw_author_name":"Ruben Zamar","raw_affiliation_strings":["University of British Columbia, Vancouver, BC, Canada"],"affiliations":[{"raw_affiliation_string":"University of British Columbia, Vancouver, BC, Canada","institution_ids":["https://openalex.org/I141945490"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5004835200"],"corresponding_institution_ids":["https://openalex.org/I141945490"],"apc_list":null,"apc_paid":null,"fwci":1.2789,"has_fulltext":false,"cited_by_count":15,"citation_normalized_percentile":{"value":0.81406629,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":96},"biblio":{"volume":null,"issue":null,"first_page":"533","last_page":"538"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11871","display_name":"Advanced Statistical Methods and Models","score":0.9983000159263611,"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"}},"topics":[{"id":"https://openalex.org/T11871","display_name":"Advanced Statistical Methods and Models","score":0.9983000159263611,"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/T10640","display_name":"Spectroscopy and Chemometric Analyses","score":0.9962000250816345,"subfield":{"id":"https://openalex.org/subfields/1602","display_name":"Analytical Chemistry"},"field":{"id":"https://openalex.org/fields/16","display_name":"Chemistry"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T12114","display_name":"Sensory Analysis and Statistical Methods","score":0.9769999980926514,"subfield":{"id":"https://openalex.org/subfields/1106","display_name":"Food Science"},"field":{"id":"https://openalex.org/fields/11","display_name":"Agricultural and Biological Sciences"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/covariance-matrix","display_name":"Covariance matrix","score":0.790544867515564},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7683345079421997},{"id":"https://openalex.org/keywords/scalability","display_name":"Scalability","score":0.7389315366744995},{"id":"https://openalex.org/keywords/robustness","display_name":"Robustness (evolution)","score":0.7383163571357727},{"id":"https://openalex.org/keywords/curse-of-dimensionality","display_name":"Curse of dimensionality","score":0.7379622459411621},{"id":"https://openalex.org/keywords/computation","display_name":"Computation","score":0.6471009850502014},{"id":"https://openalex.org/keywords/covariance","display_name":"Covariance","score":0.5793829560279846},{"id":"https://openalex.org/keywords/outlier","display_name":"Outlier","score":0.5513432621955872},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.5075489282608032},{"id":"https://openalex.org/keywords/parallel-computing","display_name":"Parallel computing","score":0.4433438777923584},{"id":"https://openalex.org/keywords/correlation","display_name":"Correlation","score":0.44323277473449707},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.3597956895828247},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.166126549243927},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.1638711392879486},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.1587301790714264},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.07949629426002502}],"concepts":[{"id":"https://openalex.org/C185142706","wikidata":"https://www.wikidata.org/wiki/Q1134404","display_name":"Covariance matrix","level":2,"score":0.790544867515564},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7683345079421997},{"id":"https://openalex.org/C48044578","wikidata":"https://www.wikidata.org/wiki/Q727490","display_name":"Scalability","level":2,"score":0.7389315366744995},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.7383163571357727},{"id":"https://openalex.org/C111030470","wikidata":"https://www.wikidata.org/wiki/Q1430460","display_name":"Curse of dimensionality","level":2,"score":0.7379622459411621},{"id":"https://openalex.org/C45374587","wikidata":"https://www.wikidata.org/wiki/Q12525525","display_name":"Computation","level":2,"score":0.6471009850502014},{"id":"https://openalex.org/C178650346","wikidata":"https://www.wikidata.org/wiki/Q201984","display_name":"Covariance","level":2,"score":0.5793829560279846},{"id":"https://openalex.org/C79337645","wikidata":"https://www.wikidata.org/wiki/Q779824","display_name":"Outlier","level":2,"score":0.5513432621955872},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.5075489282608032},{"id":"https://openalex.org/C173608175","wikidata":"https://www.wikidata.org/wiki/Q232661","display_name":"Parallel computing","level":1,"score":0.4433438777923584},{"id":"https://openalex.org/C117220453","wikidata":"https://www.wikidata.org/wiki/Q5172842","display_name":"Correlation","level":2,"score":0.44323277473449707},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3597956895828247},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.166126549243927},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.1638711392879486},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.1587301790714264},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.07949629426002502},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0},{"id":"https://openalex.org/C77088390","wikidata":"https://www.wikidata.org/wiki/Q8513","display_name":"Database","level":1,"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/C55493867","wikidata":"https://www.wikidata.org/wiki/Q7094","display_name":"Biochemistry","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/1014052.1014115","is_oa":false,"landing_page_url":"https://doi.org/10.1145/1014052.1014115","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the tenth ACM SIGKDD international conference on Knowledge discovery and data mining","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":22,"referenced_works":["https://openalex.org/W127204279","https://openalex.org/W132711133","https://openalex.org/W1487296965","https://openalex.org/W1575350781","https://openalex.org/W1966234748","https://openalex.org/W1979573625","https://openalex.org/W1980262437","https://openalex.org/W1988374326","https://openalex.org/W1989638282","https://openalex.org/W2009144907","https://openalex.org/W2011654941","https://openalex.org/W2035180740","https://openalex.org/W2049454545","https://openalex.org/W2052740976","https://openalex.org/W2075381877","https://openalex.org/W2120490947","https://openalex.org/W2129249398","https://openalex.org/W2146225536","https://openalex.org/W2151810496","https://openalex.org/W2152139142","https://openalex.org/W2152701363","https://openalex.org/W2752885492"],"related_works":["https://openalex.org/W4296209631","https://openalex.org/W3097449145","https://openalex.org/W3006513224","https://openalex.org/W2561617217","https://openalex.org/W2046456988","https://openalex.org/W2357409937","https://openalex.org/W2085143107","https://openalex.org/W2886934452","https://openalex.org/W1489099099","https://openalex.org/W2024369332"],"abstract_inverted_index":{"The":[0],"computation":[1],"of":[2,52,69,97,101,110,128,136,186,199],"covariance":[3,19],"and":[4,14,20,33,59,83,124,153],"correlation":[5,21],"matrices":[6,22],"are":[7,23,155],"critical":[8],"to":[9,26,107],"many":[10,147],"data":[11,95,148],"mining":[12,149],"applications":[13],"processes.":[15],"Unfortunately":[16],"the":[17,34,50,53,57,60,84,98,126,133,137,164,172,175,179,192],"classical":[18],"very":[24],"sensitive":[25],"outliers.":[27],"Robust":[28],"methods,":[29],"such":[30],"as":[31],"QC":[32,44,82,152,162],"Maronna":[35,61,85,154,176],"method,":[36],"have":[37],"been":[38],"proposed.":[39],"However,":[40],"existing":[41],"algorithms":[42,79,91],"for":[43,80,146,167],"only":[45],"give":[46],"acceptable":[47],"performance":[48],"when":[49,182,191],"dimensionality":[51,123],"matrix":[54,109],"is":[55,63,163,178,188],"in":[56,66,122,125],"hundreds;":[58],"method":[62,177],"rarely":[64],"used":[65],"practice":[67],"because":[68],"its":[70],"high":[71,184,197],"computational":[72],"cost.In":[73],"this":[74],"paper,":[75],"we":[76,119,143],"develop":[77],"parallel":[78,90,134,169,193],"both":[81,151],"method.":[86],"We":[87,130],"evaluate":[88],"these":[89],"using":[92],"a":[93,108,183,196],"real":[94],"set":[96],"gene":[99],"expression":[100],"over":[102,111],"6,000":[103],"genes,":[104],"giving":[105],"rise":[106],"18":[112],"million":[113],"entries.":[114],"In":[115],"our":[116],"experimental":[117],"evaluation,":[118],"explore":[120],"scalability":[121],"number":[127,198],"processors.":[129,200],"also":[131],"compare":[132],"behaviours":[135],"two":[138],"methods.":[139],"After":[140],"thorough":[141],"experimentation,":[142],"conclude":[144],"that":[145],"applications,":[150],"viable":[156],"options.":[157],"Less":[158],"robust,":[159],"but":[160],"faster,":[161],"recommended":[165,180],"choice":[166,181],"small":[168],"platforms.":[170],"On":[171],"other":[173],"hand,":[174],"degree":[185],"robustness":[187],"required,":[189],"or":[190],"platform":[194],"features":[195]},"counts_by_year":[{"year":2022,"cited_by_count":1},{"year":2018,"cited_by_count":2},{"year":2015,"cited_by_count":1},{"year":2013,"cited_by_count":2},{"year":2012,"cited_by_count":2}],"updated_date":"2026-04-04T16:13:02.066488","created_date":"2025-10-10T00:00:00"}