{"id":"https://openalex.org/W4413277552","doi":"https://doi.org/10.1109/lsp.2025.3599784","title":"Tuning-Free Online Robust Principal Component Analysis Through Implicit Regularization","display_name":"Tuning-Free Online Robust Principal Component Analysis Through Implicit Regularization","publication_year":2025,"publication_date":"2025-01-01","ids":{"openalex":"https://openalex.org/W4413277552","doi":"https://doi.org/10.1109/lsp.2025.3599784"},"language":"en","primary_location":{"id":"doi:10.1109/lsp.2025.3599784","is_oa":false,"landing_page_url":"https://doi.org/10.1109/lsp.2025.3599784","pdf_url":null,"source":{"id":"https://openalex.org/S120629676","display_name":"IEEE Signal Processing Letters","issn_l":"1070-9908","issn":["1070-9908","1558-2361"],"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 Signal Processing Letters","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/A5034668330","display_name":"Lakshmi Jayalal","orcid":null},"institutions":[{"id":"https://openalex.org/I24676775","display_name":"Indian Institute of Technology Madras","ror":"https://ror.org/03v0r5n49","country_code":"IN","type":"facility","lineage":["https://openalex.org/I24676775"]}],"countries":["IN"],"is_corresponding":true,"raw_author_name":"Lakshmi Jayalal","raw_affiliation_strings":["Department of Electrical Engineering, Indian Institute of Technology Madras, Chennai, India"],"affiliations":[{"raw_affiliation_string":"Department of Electrical Engineering, Indian Institute of Technology Madras, Chennai, India","institution_ids":["https://openalex.org/I24676775"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5002631341","display_name":"Gokularam Muthukrishnan","orcid":null},"institutions":[{"id":"https://openalex.org/I24676775","display_name":"Indian Institute of Technology Madras","ror":"https://ror.org/03v0r5n49","country_code":"IN","type":"facility","lineage":["https://openalex.org/I24676775"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Gokularam Muthukrishnan","raw_affiliation_strings":["Department of Electrical Engineering, Indian Institute of Technology Madras, Chennai, India"],"affiliations":[{"raw_affiliation_string":"Department of Electrical Engineering, Indian Institute of Technology Madras, Chennai, India","institution_ids":["https://openalex.org/I24676775"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5046290878","display_name":"Sheetal Kalyani","orcid":"https://orcid.org/0000-0002-1530-0140"},"institutions":[{"id":"https://openalex.org/I24676775","display_name":"Indian Institute of Technology Madras","ror":"https://ror.org/03v0r5n49","country_code":"IN","type":"facility","lineage":["https://openalex.org/I24676775"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Sheetal Kalyani","raw_affiliation_strings":["Department of Electrical Engineering, Indian Institute of Technology Madras, Chennai, India"],"affiliations":[{"raw_affiliation_string":"Department of Electrical Engineering, Indian Institute of Technology Madras, Chennai, India","institution_ids":["https://openalex.org/I24676775"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5034668330"],"corresponding_institution_ids":["https://openalex.org/I24676775"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.31035923,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"32","issue":null,"first_page":"3360","last_page":"3364"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11447","display_name":"Blind Source Separation Techniques","score":0.984499990940094,"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"}},"topics":[{"id":"https://openalex.org/T11447","display_name":"Blind Source Separation Techniques","score":0.984499990940094,"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/T10876","display_name":"Fault Detection and Control Systems","score":0.9704999923706055,"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/T11236","display_name":"Control Systems and Identification","score":0.9595000147819519,"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/principal-component-analysis","display_name":"Principal component analysis","score":0.776418924331665},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6031171679496765},{"id":"https://openalex.org/keywords/regularization","display_name":"Regularization (linguistics)","score":0.5181028246879578},{"id":"https://openalex.org/keywords/robustness","display_name":"Robustness (evolution)","score":0.47583818435668945},{"id":"https://openalex.org/keywords/component","display_name":"Component (thermodynamics)","score":0.44077038764953613},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.41231846809387207},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.34094470739364624},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.3342888653278351}],"concepts":[{"id":"https://openalex.org/C27438332","wikidata":"https://www.wikidata.org/wiki/Q2873","display_name":"Principal component analysis","level":2,"score":0.776418924331665},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6031171679496765},{"id":"https://openalex.org/C2776135515","wikidata":"https://www.wikidata.org/wiki/Q17143721","display_name":"Regularization (linguistics)","level":2,"score":0.5181028246879578},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.47583818435668945},{"id":"https://openalex.org/C168167062","wikidata":"https://www.wikidata.org/wiki/Q1117970","display_name":"Component (thermodynamics)","level":2,"score":0.44077038764953613},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.41231846809387207},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.34094470739364624},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.3342888653278351},{"id":"https://openalex.org/C97355855","wikidata":"https://www.wikidata.org/wiki/Q11473","display_name":"Thermodynamics","level":1,"score":0.0},{"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},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/lsp.2025.3599784","is_oa":false,"landing_page_url":"https://doi.org/10.1109/lsp.2025.3599784","pdf_url":null,"source":{"id":"https://openalex.org/S120629676","display_name":"IEEE Signal Processing Letters","issn_l":"1070-9908","issn":["1070-9908","1558-2361"],"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 Signal Processing Letters","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":16,"referenced_works":["https://openalex.org/W1998925295","https://openalex.org/W2096642693","https://openalex.org/W2118550318","https://openalex.org/W2119692864","https://openalex.org/W2145962650","https://openalex.org/W2566079294","https://openalex.org/W2591340095","https://openalex.org/W2890388200","https://openalex.org/W2894516756","https://openalex.org/W2951401720","https://openalex.org/W2964047251","https://openalex.org/W4254751698","https://openalex.org/W4280524509","https://openalex.org/W4382463760","https://openalex.org/W4384202455","https://openalex.org/W4391898156"],"related_works":["https://openalex.org/W1975632186","https://openalex.org/W3027745756","https://openalex.org/W3205213561","https://openalex.org/W2531880140","https://openalex.org/W2763148304","https://openalex.org/W2036609560","https://openalex.org/W346861917","https://openalex.org/W3024018414","https://openalex.org/W2126145365","https://openalex.org/W2373052636"],"abstract_inverted_index":{"The":[0],"performance":[1],"of":[2,11,53,71,81,96],"(OR-PCA)":[3],"technique":[4],"heavily":[5],"depends":[6],"on":[7,33,114],"the":[8,12,31,79,110,122],"optimum":[9],"tuning":[10,16,35],"explicit":[13],"regularizers.":[14],"This":[15],"is":[17],"dataset-sensitive":[18],"and":[19,62,106,116],"often":[20],"impractical":[21],"to":[22,29,58],"optimize":[23],"in":[24,65,78,88,109],"real-world":[25,117],"scenarios.":[26],"We":[27],"aim":[28],"remove":[30],"dependency":[32],"these":[34],"parameters":[36],"by":[37],"using":[38],"implicit":[39,50],"regularization.":[40],"To":[41],"this":[42],"end,":[43],"we":[44],"develop":[45],"an":[46],"approach":[47],"that":[48,100,121],"integrates":[49],"regularization":[51],"properties":[52],"various":[54],"gradient":[55,98],"descent":[56,99],"methods":[57],"estimate":[59],"sparse":[60],"outliers":[61],"low-dimensional":[63],"representations":[64],"a":[66,82],"streaming":[67],"setting\u2014a":[68],"non-trivial":[69],"extension":[70],"existing":[72,129],"techniques.":[73],"A":[74],"key":[75],"novelty":[76],"lies":[77],"design":[80],"new":[83],"parameterization":[84],"for":[85,137],"matrix":[86],"estimation":[87],"OR-PCA.":[89],"Our":[90],"method":[91],"incorporates":[92],"three":[93],"different":[94],"versions":[95],"modified":[97],"separate":[101],"but":[102],"naturally":[103],"encourage":[104],"sparsity":[105],"low-rank":[107],"structures":[108],"data.":[111],"Experimental":[112],"results":[113],"synthetic":[115],"video":[118],"datasets":[119],"demonstrate":[120],"proposed":[123],"method,":[124],"namely,":[125],"OR-PCA":[126,130],"(TF-ORPCA),":[127],"outperforms":[128],"methods.":[131],"TF-ORPCA":[132],"makes":[133],"it":[134],"more":[135],"scalable":[136],"large":[138],"datasets.":[139]},"counts_by_year":[],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
