{"id":"https://openalex.org/W3034985331","doi":"https://doi.org/10.1109/sam48682.2020.9104268","title":"Online Robust Reduced-Rank Regression","display_name":"Online Robust Reduced-Rank Regression","publication_year":2020,"publication_date":"2020-06-01","ids":{"openalex":"https://openalex.org/W3034985331","doi":"https://doi.org/10.1109/sam48682.2020.9104268","mag":"3034985331"},"language":"en","primary_location":{"id":"doi:10.1109/sam48682.2020.9104268","is_oa":false,"landing_page_url":"https://doi.org/10.1109/sam48682.2020.9104268","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 IEEE 11th Sensor Array and Multichannel Signal Processing Workshop (SAM)","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/A5086438443","display_name":"Yangzhuoran Fin Yang","orcid":"https://orcid.org/0000-0002-1232-8017"},"institutions":[{"id":"https://openalex.org/I56590836","display_name":"Monash University","ror":"https://ror.org/02bfwt286","country_code":"AU","type":"education","lineage":["https://openalex.org/I56590836"]}],"countries":["AU"],"is_corresponding":false,"raw_author_name":"Yangzhuoran Fin Yang","raw_affiliation_strings":["Department of Econometrics and Business Statistics, Monash University, Melbourne, Australia"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Econometrics and Business Statistics, Monash University, Melbourne, Australia","institution_ids":["https://openalex.org/I56590836"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5074721617","display_name":"Ziping Zhao","orcid":"https://orcid.org/0000-0002-8668-6263"},"institutions":[{"id":"https://openalex.org/I30809798","display_name":"ShanghaiTech University","ror":"https://ror.org/030bhh786","country_code":"CN","type":"education","lineage":["https://openalex.org/I30809798"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Ziping Zhao","raw_affiliation_strings":["School of Information Science and Technology, ShanghaiTech University, Shanghai, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Information Science and Technology, ShanghaiTech University, Shanghai, China","institution_ids":["https://openalex.org/I30809798"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":{"value":0.06600219,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":94,"max":96},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"5"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10500","display_name":"Sparse and Compressive Sensing Techniques","score":0.9987999796867371,"subfield":{"id":"https://openalex.org/subfields/2206","display_name":"Computational Mechanics"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T10500","display_name":"Sparse and Compressive Sensing Techniques","score":0.9987999796867371,"subfield":{"id":"https://openalex.org/subfields/2206","display_name":"Computational Mechanics"},"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/T11871","display_name":"Advanced Statistical Methods and Models","score":0.998199999332428,"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/T10136","display_name":"Statistical Methods and Inference","score":0.9962000250816345,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/outlier","display_name":"Outlier","score":0.7520783543586731},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.657802939414978},{"id":"https://openalex.org/keywords/robustness","display_name":"Robustness (evolution)","score":0.6434087157249451},{"id":"https://openalex.org/keywords/robust-regression","display_name":"Robust regression","score":0.531771719455719},{"id":"https://openalex.org/keywords/least-absolute-deviations","display_name":"Least absolute deviations","score":0.4685229957103729},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.4470788240432739},{"id":"https://openalex.org/keywords/big-data","display_name":"Big data","score":0.4202226996421814},{"id":"https://openalex.org/keywords/mathematical-optimization","display_name":"Mathematical optimization","score":0.3632550537586212},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.35621416568756104},{"id":"https://openalex.org/keywords/regression","display_name":"Regression","score":0.3211019039154053},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.25101086497306824},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.2450105845928192},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.21064722537994385}],"concepts":[{"id":"https://openalex.org/C79337645","wikidata":"https://www.wikidata.org/wiki/Q779824","display_name":"Outlier","level":2,"score":0.7520783543586731},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.657802939414978},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.6434087157249451},{"id":"https://openalex.org/C70259352","wikidata":"https://www.wikidata.org/wiki/Q1847839","display_name":"Robust regression","level":3,"score":0.531771719455719},{"id":"https://openalex.org/C31441030","wikidata":"https://www.wikidata.org/wiki/Q4291882","display_name":"Least absolute deviations","level":3,"score":0.4685229957103729},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.4470788240432739},{"id":"https://openalex.org/C75684735","wikidata":"https://www.wikidata.org/wiki/Q858810","display_name":"Big data","level":2,"score":0.4202226996421814},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.3632550537586212},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.35621416568756104},{"id":"https://openalex.org/C83546350","wikidata":"https://www.wikidata.org/wiki/Q1139051","display_name":"Regression","level":2,"score":0.3211019039154053},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.25101086497306824},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.2450105845928192},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.21064722537994385},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","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/C55493867","wikidata":"https://www.wikidata.org/wiki/Q7094","display_name":"Biochemistry","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/sam48682.2020.9104268","is_oa":false,"landing_page_url":"https://doi.org/10.1109/sam48682.2020.9104268","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 IEEE 11th Sensor Array and Multichannel Signal Processing Workshop (SAM)","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":37,"referenced_works":["https://openalex.org/W171393630","https://openalex.org/W1490324987","https://openalex.org/W1491719355","https://openalex.org/W1549482393","https://openalex.org/W1963912781","https://openalex.org/W1975273219","https://openalex.org/W1975832370","https://openalex.org/W1985658808","https://openalex.org/W1986014851","https://openalex.org/W2002124338","https://openalex.org/W2012712694","https://openalex.org/W2034133761","https://openalex.org/W2034707435","https://openalex.org/W2054121219","https://openalex.org/W2060488580","https://openalex.org/W2087936817","https://openalex.org/W2097886685","https://openalex.org/W2110603299","https://openalex.org/W2132211083","https://openalex.org/W2144089967","https://openalex.org/W2165933227","https://openalex.org/W2180060173","https://openalex.org/W2464749053","https://openalex.org/W2582533304","https://openalex.org/W2766292535","https://openalex.org/W2912400541","https://openalex.org/W2947626232","https://openalex.org/W2962967935","https://openalex.org/W2963363119","https://openalex.org/W2963826549","https://openalex.org/W3015387428","https://openalex.org/W3122229960","https://openalex.org/W4232524738","https://openalex.org/W4399576508","https://openalex.org/W6651013066","https://openalex.org/W6676811707","https://openalex.org/W6719963174"],"related_works":["https://openalex.org/W3121734683","https://openalex.org/W2085680114","https://openalex.org/W4210813465","https://openalex.org/W1600426151","https://openalex.org/W1974187127","https://openalex.org/W1833314573","https://openalex.org/W3121311879","https://openalex.org/W2384527366","https://openalex.org/W4311044804","https://openalex.org/W2285494230"],"abstract_inverted_index":{"The":[0,132],"reduced-rank":[1],"regression":[2],"(RRR)":[3],"model":[4,45,134],"is":[5,108,128,137],"widely":[6],"used":[7],"in":[8,56],"data":[9,58,68,80,83,116],"analytics":[10],"where":[11],"the":[12,25,43,61,73,90,93,114,123,143],"response":[13],"variables":[14],"are":[15,33,53],"believed":[16],"to":[17,66,78,111],"depend":[18],"on":[19,100,122],"a":[20,104],"few":[21],"linear":[22,31],"combinations":[23,32],"of":[24,34],"predictor":[26],"variables,":[27],"or":[28,70,82],"when":[29],"such":[30],"special":[35],"interest.":[36],"In":[37,85],"this":[38,86],"paper,":[39,87],"we":[40,88],"will":[41],"address":[42,89],"RRR":[44],"estimation":[46,62,74,97,106],"problem":[47],"by":[48,140],"considering":[49],"two":[50],"targets":[51],"which":[52],"popular":[54],"especially":[55],"big":[57],"applications:":[59],"i)":[60],"should":[63,75],"be":[64,76],"robust":[65,94],"heavytailed":[67],"distribution":[69,102],"outliers;":[71],"ii)":[72],"amenable":[77],"large-scale":[79,115],"sets":[81],"streams.":[84],"robustness":[91],"via":[92],"maximum":[95],"likelihood":[96],"procedure":[98,107],"based":[99],"Cauchy":[101],"and":[103,135],"stochastic":[105,124],"further":[109],"adopted":[110],"deal":[112],"with":[113,142],"sets.":[117],"An":[118],"efficient":[119],"algorithm":[120,136],"leveraging":[121],"majorization":[125],"minimization":[126],"method":[127],"proposed":[129,133],"for":[130],"problem-solving.":[131],"validated":[138],"numerically":[139],"comparing":[141],"state-of-the-art":[144],"methods.":[145]},"counts_by_year":[{"year":2024,"cited_by_count":2}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}
