{"id":"https://openalex.org/W2167157155","doi":"https://doi.org/10.1109/tsp.2012.2229992","title":"Analysis of Sparse Regularization Based Robust Regression Approaches","display_name":"Analysis of Sparse Regularization Based Robust Regression Approaches","publication_year":2012,"publication_date":"2012-11-27","ids":{"openalex":"https://openalex.org/W2167157155","doi":"https://doi.org/10.1109/tsp.2012.2229992","mag":"2167157155"},"language":"en","primary_location":{"id":"doi:10.1109/tsp.2012.2229992","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tsp.2012.2229992","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/A5006862080","display_name":"Kaushik Mitra","orcid":"https://orcid.org/0000-0001-6747-9050"},"institutions":[{"id":"https://openalex.org/I74775410","display_name":"Rice University","ror":"https://ror.org/008zs3103","country_code":"US","type":"education","lineage":["https://openalex.org/I74775410"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Kaushik Mitra","raw_affiliation_strings":["Department of Electrical and Computer Engineering, Rice University, Houston, TX, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Electrical and Computer Engineering, Rice University, Houston, TX, USA","institution_ids":["https://openalex.org/I74775410"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5073971393","display_name":"Ashok Veeraraghavan","orcid":"https://orcid.org/0000-0001-5043-7460"},"institutions":[{"id":"https://openalex.org/I74775410","display_name":"Rice University","ror":"https://ror.org/008zs3103","country_code":"US","type":"education","lineage":["https://openalex.org/I74775410"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Ashok Veeraraghavan","raw_affiliation_strings":["Department of Electrical and Computer Engineering, Rice University, Houston, TX, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Electrical and Computer Engineering, Rice University, Houston, TX, USA","institution_ids":["https://openalex.org/I74775410"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5102762707","display_name":"Rama Chellappa","orcid":"https://orcid.org/0000-0002-7638-1650"},"institutions":[{"id":"https://openalex.org/I66946132","display_name":"University of Maryland, College Park","ror":"https://ror.org/047s2c258","country_code":"US","type":"education","lineage":["https://openalex.org/I66946132"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Rama Chellappa","raw_affiliation_strings":["Department of Electrical and Computer Engineering, University of Maryland, College Park, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Electrical and Computer Engineering, University of Maryland, College Park, USA","institution_ids":["https://openalex.org/I66946132"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":2.042,"has_fulltext":false,"cited_by_count":38,"citation_normalized_percentile":{"value":0.86815988,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":99},"biblio":{"volume":"61","issue":"5","first_page":"1249","last_page":"1257"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10500","display_name":"Sparse and Compressive Sensing Techniques","score":1.0,"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":1.0,"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/T11447","display_name":"Blind Source Separation Techniques","score":0.9947999715805054,"subfield":{"id":"https://openalex.org/subfields/1711","display_name":"Signal Processing"},"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/T12879","display_name":"Distributed Sensor Networks and Detection Algorithms","score":0.9915000200271606,"subfield":{"id":"https://openalex.org/subfields/1705","display_name":"Computer Networks and Communications"},"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":0.5731075406074524},{"id":"https://openalex.org/keywords/subspace-topology","display_name":"Subspace topology","score":0.5520110130310059},{"id":"https://openalex.org/keywords/regression","display_name":"Regression","score":0.5076314210891724},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.4561218321323395},{"id":"https://openalex.org/keywords/regularization","display_name":"Regularization (linguistics)","score":0.443642795085907},{"id":"https://openalex.org/keywords/linear-subspace","display_name":"Linear subspace","score":0.44299134612083435},{"id":"https://openalex.org/keywords/compressed-sensing","display_name":"Compressed sensing","score":0.4422128200531006},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.4322473406791687},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.4011712968349457},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.36194026470184326},{"id":"https://openalex.org/keywords/combinatorics","display_name":"Combinatorics","score":0.32926660776138306},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.18133923411369324},{"id":"https://openalex.org/keywords/pure-mathematics","display_name":"Pure mathematics","score":0.07609698176383972}],"concepts":[{"id":"https://openalex.org/C79337645","wikidata":"https://www.wikidata.org/wiki/Q779824","display_name":"Outlier","level":2,"score":0.5731075406074524},{"id":"https://openalex.org/C32834561","wikidata":"https://www.wikidata.org/wiki/Q660730","display_name":"Subspace topology","level":2,"score":0.5520110130310059},{"id":"https://openalex.org/C83546350","wikidata":"https://www.wikidata.org/wiki/Q1139051","display_name":"Regression","level":2,"score":0.5076314210891724},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.4561218321323395},{"id":"https://openalex.org/C2776135515","wikidata":"https://www.wikidata.org/wiki/Q17143721","display_name":"Regularization (linguistics)","level":2,"score":0.443642795085907},{"id":"https://openalex.org/C12362212","wikidata":"https://www.wikidata.org/wiki/Q728435","display_name":"Linear subspace","level":2,"score":0.44299134612083435},{"id":"https://openalex.org/C124851039","wikidata":"https://www.wikidata.org/wiki/Q2665459","display_name":"Compressed sensing","level":2,"score":0.4422128200531006},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.4322473406791687},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.4011712968349457},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.36194026470184326},{"id":"https://openalex.org/C114614502","wikidata":"https://www.wikidata.org/wiki/Q76592","display_name":"Combinatorics","level":1,"score":0.32926660776138306},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.18133923411369324},{"id":"https://openalex.org/C202444582","wikidata":"https://www.wikidata.org/wiki/Q837863","display_name":"Pure mathematics","level":1,"score":0.07609698176383972}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/tsp.2012.2229992","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tsp.2012.2229992","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:CiteSeerX.psu:10.1.1.643.9386","is_oa":false,"landing_page_url":"http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.643.9386","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"http://www.ece.rice.edu/~av21/Documents/2013/Analysis of Sparse Regularization Based Robust.pdf","raw_type":"text"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":34,"referenced_works":["https://openalex.org/W36711357","https://openalex.org/W1986931325","https://openalex.org/W2010016312","https://openalex.org/W2010669260","https://openalex.org/W2011627547","https://openalex.org/W2014896416","https://openalex.org/W2015418199","https://openalex.org/W2032520928","https://openalex.org/W2046434485","https://openalex.org/W2066890711","https://openalex.org/W2078776517","https://openalex.org/W2085261163","https://openalex.org/W2105235982","https://openalex.org/W2109921208","https://openalex.org/W2115275122","https://openalex.org/W2116437043","https://openalex.org/W2129131372","https://openalex.org/W2129249398","https://openalex.org/W2145096794","https://openalex.org/W2148154358","https://openalex.org/W2152701363","https://openalex.org/W2161310686","https://openalex.org/W2170507371","https://openalex.org/W2296616510","https://openalex.org/W2489822048","https://openalex.org/W2498464397","https://openalex.org/W2498631646","https://openalex.org/W2798909945","https://openalex.org/W2963899927","https://openalex.org/W4242010931","https://openalex.org/W4250955649","https://openalex.org/W4255230573","https://openalex.org/W4285719527","https://openalex.org/W6658285354"],"related_works":["https://openalex.org/W3100286349","https://openalex.org/W2896134808","https://openalex.org/W3172436493","https://openalex.org/W4287164812","https://openalex.org/W2957492749","https://openalex.org/W1995723671","https://openalex.org/W1887135636","https://openalex.org/W2386063599","https://openalex.org/W1975884855","https://openalex.org/W3213150849"],"abstract_inverted_index":{"Regression":[0],"in":[1],"the":[2,48,54,61,68,71,77,96,101,121,128,133,145,150,165,169,180],"presence":[3],"of":[4,56,63,70,152,157,164,167],"outliers":[5,168],"is":[6,58,74,144],"an":[7,162],"inherently":[8],"combinatorial":[9,18],"problem.":[10,124],"However,":[11],"compressive":[12],"sensing":[13],"theory":[14],"suggests":[15],"that":[16,127,148],"certain":[17],"optimization":[19],"problems":[20],"can":[21,174],"be":[22],"exactly":[23],"solved":[24],"using":[25],"polynomial-time":[26,37],"algorithms.":[27,154],"Motivated":[28],"by":[29,76],"this":[30,43,158],"connection,":[31],"several":[32],"research":[33],"groups":[34],"have":[35],"proposed":[36],"algorithms":[38,197,203],"for":[39,204],"robust":[40,50,122,195],"regression.":[41],"In":[42,155],"paper":[44],"we":[45,160],"specifically":[46],"address":[47],"traditional":[49,194],"regression":[51,65,123,196,206],"problem,":[52],"where":[53],"number":[55,62,166],"observations":[57],"more":[59],"than":[60],"unknown":[64],"parameters":[66],"and":[67,111,136,201],"structure":[69],"regressor":[72,134],"matrix":[73],"defined":[75],"training":[78],"dataset":[79],"(and":[80],"hence":[81],"it":[82],"may":[83],"not":[84],"satisfy":[85],"properties":[86],"such":[87],"as":[88],"Restricted":[89],"Isometry":[90],"Property":[91],"or":[92],"incoherence).":[93],"We":[94,125,176],"derive":[95],"precise":[97],"conditions":[98],"under":[99],"which":[100],"sparse":[102,170,181],"regularization":[103,171,190],"(":[104,182],"<i":[105,112,138,183],"xmlns:mml=\"http://www.w3.org/1998/Math/MathML\"":[106,109,113,116,139,184,187],"xmlns:xlink=\"http://www.w3.org/1999/xlink\">l</i>":[107,114,185],"<sub":[108,115,186],"xmlns:xlink=\"http://www.w3.org/1999/xlink\">0</sub>":[110],"xmlns:xlink=\"http://www.w3.org/1999/xlink\">1</sub>":[117,188],"-norm)":[118,189],"approaches":[119,173],"solve":[120],"show":[126],"smallest":[129],"principal":[130],"angle":[131,159],"between":[132],"subspace":[135],"all":[137],"xmlns:xlink=\"http://www.w3.org/1999/xlink\">k</i>":[140],"-dimensional":[141],"outlier":[142],"subspaces":[143],"fundamental":[146],"quantity":[147],"determines":[149],"performance":[151],"these":[153],"terms":[156],"provide":[161],"estimate":[163],"based":[172],"handle.":[175],"then":[177],"empirically":[178],"evaluate":[179],"approach":[191],"against":[192],"other":[193],"to":[198],"identify":[199],"accurate":[200],"efficient":[202],"high-dimensional":[205],"problems.":[207]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":2},{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":4},{"year":2022,"cited_by_count":3},{"year":2021,"cited_by_count":1},{"year":2020,"cited_by_count":3},{"year":2019,"cited_by_count":2},{"year":2018,"cited_by_count":1},{"year":2017,"cited_by_count":6},{"year":2016,"cited_by_count":8},{"year":2015,"cited_by_count":4},{"year":2014,"cited_by_count":2}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
