{"id":"https://openalex.org/W2770490380","doi":"https://doi.org/10.1109/tsp.2017.2771720","title":"Robust Linear Regression via $\\ell_0$ Regularization","display_name":"Robust Linear Regression via $\\ell_0$ Regularization","publication_year":2017,"publication_date":"2017-11-28","ids":{"openalex":"https://openalex.org/W2770490380","doi":"https://doi.org/10.1109/tsp.2017.2771720","mag":"2770490380"},"language":"en","primary_location":{"id":"doi:10.1109/tsp.2017.2771720","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tsp.2017.2771720","pdf_url":null,"source":{"id":"https://openalex.org/S168680287","display_name":"IEEE Transactions on Signal Processing","issn_l":"1053-587X","issn":["1053-587X","1941-0476"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["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 Signal Processing","raw_type":"journal-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/A5100374974","display_name":"Jing Liu","orcid":"https://orcid.org/0000-0002-1712-2966"},"institutions":[{"id":"https://openalex.org/I36258959","display_name":"University of California San Diego","ror":"https://ror.org/0168r3w48","country_code":"US","type":"education","lineage":["https://openalex.org/I36258959"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Jing Liu","raw_affiliation_strings":["Department of Electrical and Computer Engineering, University of California, San Diego, CA, USA"],"affiliations":[{"raw_affiliation_string":"Department of Electrical and Computer Engineering, University of California, San Diego, CA, USA","institution_ids":["https://openalex.org/I36258959"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5068804724","display_name":"Pamela C. Cosman","orcid":"https://orcid.org/0000-0002-4012-0176"},"institutions":[{"id":"https://openalex.org/I36258959","display_name":"University of California San Diego","ror":"https://ror.org/0168r3w48","country_code":"US","type":"education","lineage":["https://openalex.org/I36258959"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Pamela C. Cosman","raw_affiliation_strings":["Department of Electrical and Computer Engineering, University of California, San Diego, CA, USA"],"affiliations":[{"raw_affiliation_string":"Department of Electrical and Computer Engineering, University of California, San Diego, CA, USA","institution_ids":["https://openalex.org/I36258959"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5001700017","display_name":"Bhaskar D. Rao","orcid":"https://orcid.org/0000-0001-6357-689X"},"institutions":[{"id":"https://openalex.org/I36258959","display_name":"University of California San Diego","ror":"https://ror.org/0168r3w48","country_code":"US","type":"education","lineage":["https://openalex.org/I36258959"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Bhaskar D. Rao","raw_affiliation_strings":["Department of Electrical and Computer Engineering, University of California, San Diego, CA, USA"],"affiliations":[{"raw_affiliation_string":"Department of Electrical and Computer Engineering, University of California, San Diego, CA, USA","institution_ids":["https://openalex.org/I36258959"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5100374974"],"corresponding_institution_ids":["https://openalex.org/I36258959"],"apc_list":null,"apc_paid":null,"fwci":3.7035,"has_fulltext":false,"cited_by_count":43,"citation_normalized_percentile":{"value":0.93447758,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":94,"max":99},"biblio":{"volume":"66","issue":"3","first_page":"698","last_page":"713"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10500","display_name":"Sparse and Compressive Sensing Techniques","score":0.9998999834060669,"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":0.9998999834060669,"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/T10534","display_name":"Structural Health Monitoring Techniques","score":0.9937000274658203,"subfield":{"id":"https://openalex.org/subfields/2205","display_name":"Civil and Structural 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/T11871","display_name":"Advanced Statistical Methods and Models","score":0.9872999787330627,"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":0.9011801481246948},{"id":"https://openalex.org/keywords/robust-statistics","display_name":"Robust statistics","score":0.6340960264205933},{"id":"https://openalex.org/keywords/estimator","display_name":"Estimator","score":0.6076452136039734},{"id":"https://openalex.org/keywords/regularization","display_name":"Regularization (linguistics)","score":0.5676745176315308},{"id":"https://openalex.org/keywords/robust-regression","display_name":"Robust regression","score":0.504198431968689},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.4959658086299896},{"id":"https://openalex.org/keywords/bounded-function","display_name":"Bounded function","score":0.46223267912864685},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.45934611558914185},{"id":"https://openalex.org/keywords/robustness","display_name":"Robustness (evolution)","score":0.45824334025382996},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.4547024667263031},{"id":"https://openalex.org/keywords/norm","display_name":"Norm (philosophy)","score":0.42365431785583496},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.34312158823013306},{"id":"https://openalex.org/keywords/mathematical-optimization","display_name":"Mathematical optimization","score":0.3417309522628784},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.32143983244895935},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.1520017385482788}],"concepts":[{"id":"https://openalex.org/C79337645","wikidata":"https://www.wikidata.org/wiki/Q779824","display_name":"Outlier","level":2,"score":0.9011801481246948},{"id":"https://openalex.org/C67226441","wikidata":"https://www.wikidata.org/wiki/Q1665389","display_name":"Robust statistics","level":3,"score":0.6340960264205933},{"id":"https://openalex.org/C185429906","wikidata":"https://www.wikidata.org/wiki/Q1130160","display_name":"Estimator","level":2,"score":0.6076452136039734},{"id":"https://openalex.org/C2776135515","wikidata":"https://www.wikidata.org/wiki/Q17143721","display_name":"Regularization (linguistics)","level":2,"score":0.5676745176315308},{"id":"https://openalex.org/C70259352","wikidata":"https://www.wikidata.org/wiki/Q1847839","display_name":"Robust regression","level":3,"score":0.504198431968689},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.4959658086299896},{"id":"https://openalex.org/C34388435","wikidata":"https://www.wikidata.org/wiki/Q2267362","display_name":"Bounded function","level":2,"score":0.46223267912864685},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.45934611558914185},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.45824334025382996},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.4547024667263031},{"id":"https://openalex.org/C191795146","wikidata":"https://www.wikidata.org/wiki/Q3878446","display_name":"Norm (philosophy)","level":2,"score":0.42365431785583496},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.34312158823013306},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.3417309522628784},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.32143983244895935},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.1520017385482788},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0},{"id":"https://openalex.org/C17744445","wikidata":"https://www.wikidata.org/wiki/Q36442","display_name":"Political science","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/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0},{"id":"https://openalex.org/C199539241","wikidata":"https://www.wikidata.org/wiki/Q7748","display_name":"Law","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}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/tsp.2017.2771720","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tsp.2017.2771720","pdf_url":null,"source":{"id":"https://openalex.org/S168680287","display_name":"IEEE Transactions on Signal Processing","issn_l":"1053-587X","issn":["1053-587X","1941-0476"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["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 Signal Processing","raw_type":"journal-article"},{"id":"pmh:oai:escholarship.org:ark:/13030/qt3v25d7x2","is_oa":false,"landing_page_url":"https://escholarship.org/uc/item/3v25d7x2","pdf_url":null,"source":{"id":"https://openalex.org/S4306400115","display_name":"eScholarship (California Digital Library)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I2801248553","host_organization_name":"California Digital Library","host_organization_lineage":["https://openalex.org/I2801248553"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"IEEE Transactions on Signal Processing, vol 66, iss 3","raw_type":"article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":55,"referenced_works":["https://openalex.org/W149129625","https://openalex.org/W616376197","https://openalex.org/W1591116419","https://openalex.org/W1683291642","https://openalex.org/W1969515697","https://openalex.org/W1971334823","https://openalex.org/W1986931325","https://openalex.org/W2012712694","https://openalex.org/W2014896416","https://openalex.org/W2033130658","https://openalex.org/W2033894760","https://openalex.org/W2034260606","https://openalex.org/W2044101683","https://openalex.org/W2050551672","https://openalex.org/W2057690238","https://openalex.org/W2066890711","https://openalex.org/W2068302187","https://openalex.org/W2075506710","https://openalex.org/W2078776517","https://openalex.org/W2085261163","https://openalex.org/W2089493818","https://openalex.org/W2096586829","https://openalex.org/W2097323375","https://openalex.org/W2101223300","https://openalex.org/W2105235982","https://openalex.org/W2107861471","https://openalex.org/W2109921208","https://openalex.org/W2127271355","https://openalex.org/W2128659236","https://openalex.org/W2129131372","https://openalex.org/W2129249398","https://openalex.org/W2145096794","https://openalex.org/W2147656689","https://openalex.org/W2148154358","https://openalex.org/W2152701363","https://openalex.org/W2155681181","https://openalex.org/W2156686555","https://openalex.org/W2161310686","https://openalex.org/W2164452299","https://openalex.org/W2167157155","https://openalex.org/W2168745297","https://openalex.org/W2489822048","https://openalex.org/W2498631646","https://openalex.org/W2963899927","https://openalex.org/W3006068376","https://openalex.org/W3105340263","https://openalex.org/W3122595916","https://openalex.org/W4210306310","https://openalex.org/W4235713725","https://openalex.org/W4242010931","https://openalex.org/W4250589301","https://openalex.org/W4250837161","https://openalex.org/W4255230573","https://openalex.org/W4285719527","https://openalex.org/W6619198760"],"related_works":["https://openalex.org/W3121734683","https://openalex.org/W2046343964","https://openalex.org/W1600426151","https://openalex.org/W3121311879","https://openalex.org/W1539940077","https://openalex.org/W1974187127","https://openalex.org/W1506656464","https://openalex.org/W3046360373","https://openalex.org/W3124768854","https://openalex.org/W2085680114"],"abstract_inverted_index":{"Linear":[0],"regression":[1],"in":[2,40],"the":[3,15,68,77,88,122,126,141,153,156],"presence":[4],"of":[5,17,70,82,155],"outliers":[6,18,35,83,102,135],"is":[7,12,19,95,144],"an":[8,46],"important":[9],"problem":[10,28],"and":[11,38,84,94,115,133],"challenging":[13],"as":[14],"support":[16,51],"not":[20],"known":[21],"beforehand.":[22],"Many":[23],"robust":[24,49],"estimators":[25],"solve":[26],"this":[27],"via":[29],"explicitly":[30],"or":[31],"implicitly":[32],"assuming":[33],"that":[34,140],"are":[36,103,136],"sparse":[37,101,134],"result":[39],"large":[41,78],"observation":[42,79],"errors.":[43],"We":[44],"propose":[45],"algorithm":[47,116],"for":[48],"outlier":[50],"identification":[52],"(AROSI)":[53],"utilizing":[54],"a":[55],"novel":[56],"objective":[57],"function":[58],"with":[59,149],"\u2113":[60,89],"<sub":[61,90],"xmlns:mml=\"http://www.w3.org/1998/Math/MathML\"":[62,91],"xmlns:xlink=\"http://www.w3.org/1999/xlink\">0</sub>":[63,92],"-\u201cnorm\u201d":[64,93],"regularization":[65],"which":[66],"models":[67],"sparsity":[69],"outliers.":[71],"The":[72],"optimization":[73],"procedure":[74],"naturally":[75],"utilizes":[76],"error":[80,143],"assumption":[81],"directly":[85],"operates":[86],"on":[87],"guaranteed":[96],"to":[97],"converge.":[98],"When":[99],"only":[100],"present":[104],"(no":[105],"dense":[106,130],"inlier":[107,131],"noise),":[108],"we":[109,138],"show":[110],"that,":[111],"under":[112],"certain":[113],"model":[114],"parameter":[117],"settings,":[118],"AROSI":[119],"can":[120],"recover":[121],"solution":[123],"exactly.":[124],"In":[125],"case,":[127],"where":[128],"both":[129],"noise":[132],"present,":[137],"prove":[139],"estimation":[142],"bounded.":[145],"Extensive":[146],"empirical":[147],"comparisons":[148],"state-of-the-art":[150],"methods":[151],"demonstrate":[152],"advantage":[154],"proposed":[157],"method.":[158]},"counts_by_year":[{"year":2025,"cited_by_count":5},{"year":2024,"cited_by_count":2},{"year":2023,"cited_by_count":5},{"year":2022,"cited_by_count":8},{"year":2021,"cited_by_count":8},{"year":2020,"cited_by_count":7},{"year":2019,"cited_by_count":2},{"year":2018,"cited_by_count":6}],"updated_date":"2026-04-05T17:49:38.594831","created_date":"2025-10-10T00:00:00"}
