{"id":"https://openalex.org/W2288231974","doi":"https://doi.org/10.1109/cdc.2015.7402518","title":"Outlier robust kernel-based system identification using \u2113&lt;inf&gt;1&lt;/inf&gt;-Laplace techniques","display_name":"Outlier robust kernel-based system identification using \u2113&lt;inf&gt;1&lt;/inf&gt;-Laplace techniques","publication_year":2015,"publication_date":"2015-12-01","ids":{"openalex":"https://openalex.org/W2288231974","doi":"https://doi.org/10.1109/cdc.2015.7402518","mag":"2288231974"},"language":"en","primary_location":{"id":"doi:10.1109/cdc.2015.7402518","is_oa":false,"landing_page_url":"https://doi.org/10.1109/cdc.2015.7402518","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2015 54th IEEE Conference on Decision and Control (CDC)","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/A5000544193","display_name":"Giulio Bottegal","orcid":"https://orcid.org/0000-0003-3315-8704"},"institutions":[{"id":"https://openalex.org/I86987016","display_name":"KTH Royal Institute of Technology","ror":"https://ror.org/026vcq606","country_code":"SE","type":"education","lineage":["https://openalex.org/I86987016"]}],"countries":["SE"],"is_corresponding":true,"raw_author_name":"Giulio Bottegal","raw_affiliation_strings":["ACCESS Linnaeus Center, KTH Royal Institute of Technology, Sweden"],"affiliations":[{"raw_affiliation_string":"ACCESS Linnaeus Center, KTH Royal Institute of Technology, Sweden","institution_ids":["https://openalex.org/I86987016"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5047606099","display_name":"H\u00e5kan Hjalmarsson","orcid":"https://orcid.org/0000-0002-9368-3079"},"institutions":[{"id":"https://openalex.org/I86987016","display_name":"KTH Royal Institute of Technology","ror":"https://ror.org/026vcq606","country_code":"SE","type":"education","lineage":["https://openalex.org/I86987016"]}],"countries":["SE"],"is_corresponding":false,"raw_author_name":"Hakan Hjalmarsson","raw_affiliation_strings":["ACCESS Linnaeus Center, KTH Royal Institute of Technology, Sweden"],"affiliations":[{"raw_affiliation_string":"ACCESS Linnaeus Center, KTH Royal Institute of Technology, Sweden","institution_ids":["https://openalex.org/I86987016"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5078520641","display_name":"Alexandr Y. Aravkin","orcid":null},"institutions":[{"id":"https://openalex.org/I4210114115","display_name":"IBM Research - Thomas J. Watson Research Center","ror":"https://ror.org/0265w5591","country_code":"US","type":"facility","lineage":["https://openalex.org/I1341412227","https://openalex.org/I4210114115"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Alexandr Y. Aravkin","raw_affiliation_strings":["IBM T.J. Watson Research Center, Yorktown Heights, NY, USA"],"affiliations":[{"raw_affiliation_string":"IBM T.J. Watson Research Center, Yorktown Heights, NY, USA","institution_ids":["https://openalex.org/I4210114115"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5103084695","display_name":"Gianluigi Pillonetto","orcid":"https://orcid.org/0000-0002-1072-3144"},"institutions":[{"id":"https://openalex.org/I138689650","display_name":"University of Padua","ror":"https://ror.org/00240q980","country_code":"IT","type":"education","lineage":["https://openalex.org/I138689650"]}],"countries":["IT"],"is_corresponding":false,"raw_author_name":"Gianluigi Pillonetto","raw_affiliation_strings":["Department of Information Engineering, University of Padova, Padova, Italy"],"affiliations":[{"raw_affiliation_string":"Department of Information Engineering, University of Padova, Padova, Italy","institution_ids":["https://openalex.org/I138689650"]}]}],"institutions":[],"countries_distinct_count":3,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5000544193"],"corresponding_institution_ids":["https://openalex.org/I86987016"],"apc_list":null,"apc_paid":null,"fwci":0.6732,"has_fulltext":false,"cited_by_count":5,"citation_normalized_percentile":{"value":0.7566264,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":94,"max":97},"biblio":{"volume":null,"issue":null,"first_page":"2109","last_page":"2114"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11236","display_name":"Control Systems and Identification","score":0.9993000030517578,"subfield":{"id":"https://openalex.org/subfields/2207","display_name":"Control and Systems Engineering"},"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/T11236","display_name":"Control Systems and Identification","score":0.9993000030517578,"subfield":{"id":"https://openalex.org/subfields/2207","display_name":"Control and Systems 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/T10534","display_name":"Structural Health Monitoring Techniques","score":0.9979000091552734,"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/T10876","display_name":"Fault Detection and Control Systems","score":0.9966999888420105,"subfield":{"id":"https://openalex.org/subfields/2207","display_name":"Control and Systems Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/outlier","display_name":"Outlier","score":0.6804559230804443},{"id":"https://openalex.org/keywords/kernel","display_name":"Kernel (algebra)","score":0.6684659123420715},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5273317098617554},{"id":"https://openalex.org/keywords/kernel-density-estimation","display_name":"Kernel density estimation","score":0.4874842166900635},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.47755107283592224},{"id":"https://openalex.org/keywords/variable-kernel-density-estimation","display_name":"Variable kernel density estimation","score":0.47086015343666077},{"id":"https://openalex.org/keywords/system-identification","display_name":"System identification","score":0.42627936601638794},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.37995901703834534},{"id":"https://openalex.org/keywords/estimator","display_name":"Estimator","score":0.36459439992904663},{"id":"https://openalex.org/keywords/mathematical-optimization","display_name":"Mathematical optimization","score":0.35468757152557373},{"id":"https://openalex.org/keywords/kernel-method","display_name":"Kernel method","score":0.3240068554878235},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.2884477376937866},{"id":"https://openalex.org/keywords/data-modeling","display_name":"Data modeling","score":0.13355830311775208},{"id":"https://openalex.org/keywords/support-vector-machine","display_name":"Support vector machine","score":0.08464965224266052},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.07931232452392578}],"concepts":[{"id":"https://openalex.org/C79337645","wikidata":"https://www.wikidata.org/wiki/Q779824","display_name":"Outlier","level":2,"score":0.6804559230804443},{"id":"https://openalex.org/C74193536","wikidata":"https://www.wikidata.org/wiki/Q574844","display_name":"Kernel (algebra)","level":2,"score":0.6684659123420715},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5273317098617554},{"id":"https://openalex.org/C71134354","wikidata":"https://www.wikidata.org/wiki/Q458825","display_name":"Kernel density estimation","level":3,"score":0.4874842166900635},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.47755107283592224},{"id":"https://openalex.org/C195699287","wikidata":"https://www.wikidata.org/wiki/Q7915722","display_name":"Variable kernel density estimation","level":4,"score":0.47086015343666077},{"id":"https://openalex.org/C119247159","wikidata":"https://www.wikidata.org/wiki/Q1366192","display_name":"System identification","level":3,"score":0.42627936601638794},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.37995901703834534},{"id":"https://openalex.org/C185429906","wikidata":"https://www.wikidata.org/wiki/Q1130160","display_name":"Estimator","level":2,"score":0.36459439992904663},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.35468757152557373},{"id":"https://openalex.org/C122280245","wikidata":"https://www.wikidata.org/wiki/Q620622","display_name":"Kernel method","level":3,"score":0.3240068554878235},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.2884477376937866},{"id":"https://openalex.org/C67186912","wikidata":"https://www.wikidata.org/wiki/Q367664","display_name":"Data modeling","level":2,"score":0.13355830311775208},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.08464965224266052},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.07931232452392578},{"id":"https://openalex.org/C77088390","wikidata":"https://www.wikidata.org/wiki/Q8513","display_name":"Database","level":1,"score":0.0},{"id":"https://openalex.org/C114614502","wikidata":"https://www.wikidata.org/wiki/Q76592","display_name":"Combinatorics","level":1,"score":0.0}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.1109/cdc.2015.7402518","is_oa":false,"landing_page_url":"https://doi.org/10.1109/cdc.2015.7402518","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2015 54th IEEE Conference on Decision and Control (CDC)","raw_type":"proceedings-article"},{"id":"pmh:oai:www.research.unipd.it:11577/3188599","is_oa":false,"landing_page_url":"http://hdl.handle.net/11577/3188599","pdf_url":null,"source":{"id":"https://openalex.org/S4306402547","display_name":"Padua Research Archive (University of Padova)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I138689650","host_organization_name":"University of Padua","host_organization_lineage":["https://openalex.org/I138689650"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"info:eu-repo/semantics/conferenceObject"},{"id":"pmh:oai:www.research.unipd.it:11577/3188604","is_oa":false,"landing_page_url":"http://hdl.handle.net/11577/3188604","pdf_url":null,"source":{"id":"https://openalex.org/S4306402547","display_name":"Padua Research Archive (University of Padova)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I138689650","host_organization_name":"University of Padua","host_organization_lineage":["https://openalex.org/I138689650"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"info:eu-repo/semantics/conferenceObject"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":35,"referenced_works":["https://openalex.org/W41441124","https://openalex.org/W45374770","https://openalex.org/W178056938","https://openalex.org/W1746819321","https://openalex.org/W1965324089","https://openalex.org/W1982652137","https://openalex.org/W1986280275","https://openalex.org/W1997462664","https://openalex.org/W2001351287","https://openalex.org/W2021065610","https://openalex.org/W2037479549","https://openalex.org/W2038444696","https://openalex.org/W2049633694","https://openalex.org/W2068465303","https://openalex.org/W2078546163","https://openalex.org/W2092766760","https://openalex.org/W2093673101","https://openalex.org/W2117256357","https://openalex.org/W2119537322","https://openalex.org/W2130416410","https://openalex.org/W2135046866","https://openalex.org/W2143956139","https://openalex.org/W2146766088","https://openalex.org/W2161083632","https://openalex.org/W2898920993","https://openalex.org/W2950422530","https://openalex.org/W2950794326","https://openalex.org/W2963955564","https://openalex.org/W4211049957","https://openalex.org/W4232023503","https://openalex.org/W4251644969","https://openalex.org/W4298876635","https://openalex.org/W6601679187","https://openalex.org/W6670044896","https://openalex.org/W6674035469"],"related_works":["https://openalex.org/W2369488729","https://openalex.org/W2355371556","https://openalex.org/W2104827669","https://openalex.org/W3212687977","https://openalex.org/W2375654472","https://openalex.org/W2161690219","https://openalex.org/W2799907871","https://openalex.org/W3162207007","https://openalex.org/W2920855166","https://openalex.org/W2087391746"],"abstract_inverted_index":{"Regularized":[0],"kernel-based":[1,31,59,116,141],"methods":[2,32,120,142],"for":[3,143],"system":[4,60,145],"identification":[5,61],"have":[6],"gained":[7],"popularity":[8],"in":[9],"recent":[10],"years.":[11],"However,":[12],"current":[13],"formulations":[14],"are":[15,80,121],"not":[16],"robust":[17,58,115],"with":[18],"respect":[19],"to":[20,29,139],"outliers.":[21],"In":[22],"this":[23,48],"paper,":[24],"we":[25,53],"study":[26],"possible":[27],"solutions":[28],"robustify":[30],"that":[33,130],"rely":[34],"on":[35,99],"modeling":[36],"noise":[37],"using":[38,82,93],"the":[39,65,78,100,107,110],"Laplacian":[40,68],"probability":[41],"density":[42],"function":[43],"(pdf).":[44],"The":[45,75,103,118],"contribution":[46,105],"of":[47,67,73,106,112,125,132],"paper":[49,108],"is":[50,91,109],"two-fold.":[51],"First,":[52],"introduce":[54],"a":[55,83,86,94],"new":[56,84],"outlier":[57],"method.":[62,102],"It":[63],"exploits":[64],"representation":[66],"pdfs":[69],"as":[70],"scale":[71],"mixture":[72],"Gaussians.":[74],"hyperparameters":[76],"characterizing":[77],"problem":[79],"chosen":[81],"maximum":[85],"posteriori":[87],"estimator":[88],"whose":[89],"solution":[90],"computed":[92],"novel":[95],"iterative":[96],"scheme":[97],"based":[98],"expectation-maximization":[101],"second":[104],"review":[111],"two":[113],"other":[114],"methods.":[117],"three":[119],"compared":[122,138],"by":[123],"means":[124],"numerical":[126],"experiments,":[127],"which":[128],"show":[129],"all":[131],"them":[133],"give":[134],"substantial":[135],"performance":[136],"improvements":[137],"standard":[140],"linear":[144],"identification.":[146]},"counts_by_year":[{"year":2019,"cited_by_count":3},{"year":2018,"cited_by_count":2}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2016-06-24T00:00:00"}
