{"id":"https://openalex.org/W2611906854","doi":"https://doi.org/10.1109/globalsip.2016.7906054","title":"A dictionary based generalization of robust PCA","display_name":"A dictionary based generalization of robust PCA","publication_year":2016,"publication_date":"2016-12-01","ids":{"openalex":"https://openalex.org/W2611906854","doi":"https://doi.org/10.1109/globalsip.2016.7906054","mag":"2611906854"},"language":"en","primary_location":{"id":"doi:10.1109/globalsip.2016.7906054","is_oa":false,"landing_page_url":"https://doi.org/10.1109/globalsip.2016.7906054","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2016 IEEE Global Conference on Signal and Information Processing (GlobalSIP)","raw_type":"proceedings-article"},"type":"conference-paper","indexed_in":["arxiv","crossref"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/1902.08171","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5018625427","display_name":"Sirisha Rambhatla","orcid":"https://orcid.org/0000-0002-9389-727X"},"institutions":[{"id":"https://openalex.org/I130238516","display_name":"University of Minnesota","ror":"https://ror.org/017zqws13","country_code":"US","type":"education","lineage":["https://openalex.org/I130238516"]},{"id":"https://openalex.org/I4210101327","display_name":"Twin Cities Orthopedics","ror":"https://ror.org/01en4s460","country_code":"US","type":"healthcare","lineage":["https://openalex.org/I4210101327"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Sirisha Rambhatla","raw_affiliation_strings":["Department of Electrical and Computer Engineering, University of Minnesota-Twin Cities, Minneapolis"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Electrical and Computer Engineering, University of Minnesota-Twin Cities, Minneapolis","institution_ids":["https://openalex.org/I130238516","https://openalex.org/I4210101327"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101550432","display_name":"Xingguo Li","orcid":"https://orcid.org/0000-0002-5510-9447"},"institutions":[{"id":"https://openalex.org/I130238516","display_name":"University of Minnesota","ror":"https://ror.org/017zqws13","country_code":"US","type":"education","lineage":["https://openalex.org/I130238516"]},{"id":"https://openalex.org/I4210101327","display_name":"Twin Cities Orthopedics","ror":"https://ror.org/01en4s460","country_code":"US","type":"healthcare","lineage":["https://openalex.org/I4210101327"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Xingguo Li","raw_affiliation_strings":["Department of Electrical and Computer Engineering, University of Minnesota-Twin Cities, Minneapolis"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Electrical and Computer Engineering, University of Minnesota-Twin Cities, Minneapolis","institution_ids":["https://openalex.org/I130238516","https://openalex.org/I4210101327"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5011305900","display_name":"Jarvis Haupt","orcid":"https://orcid.org/0000-0002-1570-7071"},"institutions":[{"id":"https://openalex.org/I130238516","display_name":"University of Minnesota","ror":"https://ror.org/017zqws13","country_code":"US","type":"education","lineage":["https://openalex.org/I130238516"]},{"id":"https://openalex.org/I4210101327","display_name":"Twin Cities Orthopedics","ror":"https://ror.org/01en4s460","country_code":"US","type":"healthcare","lineage":["https://openalex.org/I4210101327"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Jarvis Haupt","raw_affiliation_strings":["Department of Electrical and Computer Engineering, University of Minnesota-Twin Cities, Minneapolis"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Electrical and Computer Engineering, University of Minnesota-Twin Cities, Minneapolis","institution_ids":["https://openalex.org/I130238516","https://openalex.org/I4210101327"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":2.6633,"has_fulltext":false,"cited_by_count":7,"citation_normalized_percentile":{"value":0.91657104,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":89,"max":96},"biblio":{"volume":"9","issue":null,"first_page":"1315","last_page":"1319"},"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":0.9987000226974487,"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/T10931","display_name":"Direction-of-Arrival Estimation Techniques","score":0.9878000020980835,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/generalization","display_name":"Generalization","score":0.7229623198509216},{"id":"https://openalex.org/keywords/rank","display_name":"Rank (graph theory)","score":0.5971569418907166},{"id":"https://openalex.org/keywords/component","display_name":"Component (thermodynamics)","score":0.5931881666183472},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5807052850723267},{"id":"https://openalex.org/keywords/sparse-matrix","display_name":"Sparse matrix","score":0.5762946605682373},{"id":"https://openalex.org/keywords/k-svd","display_name":"K-SVD","score":0.5681675672531128},{"id":"https://openalex.org/keywords/superposition-principle","display_name":"Superposition principle","score":0.5279300212860107},{"id":"https://openalex.org/keywords/decomposition","display_name":"Decomposition","score":0.4829261004924774},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.47306931018829346},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.47185513377189636},{"id":"https://openalex.org/keywords/matrix","display_name":"Matrix (chemical analysis)","score":0.4596400558948517},{"id":"https://openalex.org/keywords/regular-polygon","display_name":"Regular polygon","score":0.45860111713409424},{"id":"https://openalex.org/keywords/matrix-decomposition","display_name":"Matrix decomposition","score":0.45801371335983276},{"id":"https://openalex.org/keywords/sparse-approximation","display_name":"Sparse approximation","score":0.4480941891670227},{"id":"https://openalex.org/keywords/robust-principal-component-analysis","display_name":"Robust principal component analysis","score":0.4263038635253906},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4116588830947876},{"id":"https://openalex.org/keywords/principal-component-analysis","display_name":"Principal component analysis","score":0.3620889484882355},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.35285744071006775},{"id":"https://openalex.org/keywords/combinatorics","display_name":"Combinatorics","score":0.1305755078792572}],"concepts":[{"id":"https://openalex.org/C177148314","wikidata":"https://www.wikidata.org/wiki/Q170084","display_name":"Generalization","level":2,"score":0.7229623198509216},{"id":"https://openalex.org/C164226766","wikidata":"https://www.wikidata.org/wiki/Q7293202","display_name":"Rank (graph theory)","level":2,"score":0.5971569418907166},{"id":"https://openalex.org/C168167062","wikidata":"https://www.wikidata.org/wiki/Q1117970","display_name":"Component (thermodynamics)","level":2,"score":0.5931881666183472},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5807052850723267},{"id":"https://openalex.org/C56372850","wikidata":"https://www.wikidata.org/wiki/Q1050404","display_name":"Sparse matrix","level":3,"score":0.5762946605682373},{"id":"https://openalex.org/C154771677","wikidata":"https://www.wikidata.org/wiki/Q17098361","display_name":"K-SVD","level":3,"score":0.5681675672531128},{"id":"https://openalex.org/C27753989","wikidata":"https://www.wikidata.org/wiki/Q284885","display_name":"Superposition principle","level":2,"score":0.5279300212860107},{"id":"https://openalex.org/C124681953","wikidata":"https://www.wikidata.org/wiki/Q339062","display_name":"Decomposition","level":2,"score":0.4829261004924774},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.47306931018829346},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.47185513377189636},{"id":"https://openalex.org/C106487976","wikidata":"https://www.wikidata.org/wiki/Q685816","display_name":"Matrix (chemical analysis)","level":2,"score":0.4596400558948517},{"id":"https://openalex.org/C112680207","wikidata":"https://www.wikidata.org/wiki/Q714886","display_name":"Regular polygon","level":2,"score":0.45860111713409424},{"id":"https://openalex.org/C42355184","wikidata":"https://www.wikidata.org/wiki/Q1361088","display_name":"Matrix decomposition","level":3,"score":0.45801371335983276},{"id":"https://openalex.org/C124066611","wikidata":"https://www.wikidata.org/wiki/Q28684319","display_name":"Sparse approximation","level":2,"score":0.4480941891670227},{"id":"https://openalex.org/C2777749129","wikidata":"https://www.wikidata.org/wiki/Q17148469","display_name":"Robust principal component analysis","level":3,"score":0.4263038635253906},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4116588830947876},{"id":"https://openalex.org/C27438332","wikidata":"https://www.wikidata.org/wiki/Q2873","display_name":"Principal component analysis","level":2,"score":0.3620889484882355},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.35285744071006775},{"id":"https://openalex.org/C114614502","wikidata":"https://www.wikidata.org/wiki/Q76592","display_name":"Combinatorics","level":1,"score":0.1305755078792572},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0},{"id":"https://openalex.org/C97355855","wikidata":"https://www.wikidata.org/wiki/Q11473","display_name":"Thermodynamics","level":1,"score":0.0},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0},{"id":"https://openalex.org/C159985019","wikidata":"https://www.wikidata.org/wiki/Q181790","display_name":"Composite material","level":1,"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/C163716315","wikidata":"https://www.wikidata.org/wiki/Q901177","display_name":"Gaussian","level":2,"score":0.0},{"id":"https://openalex.org/C158693339","wikidata":"https://www.wikidata.org/wiki/Q190524","display_name":"Eigenvalues and eigenvectors","level":2,"score":0.0},{"id":"https://openalex.org/C192562407","wikidata":"https://www.wikidata.org/wiki/Q228736","display_name":"Materials science","level":0,"score":0.0},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0},{"id":"https://openalex.org/C18903297","wikidata":"https://www.wikidata.org/wiki/Q7150","display_name":"Ecology","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/globalsip.2016.7906054","is_oa":false,"landing_page_url":"https://doi.org/10.1109/globalsip.2016.7906054","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2016 IEEE Global Conference on Signal and Information Processing (GlobalSIP)","raw_type":"proceedings-article"},{"id":"pmh:oai:arXiv.org:1902.08171","is_oa":true,"landing_page_url":"http://arxiv.org/abs/1902.08171","pdf_url":"https://arxiv.org/pdf/1902.08171","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"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":"text"}],"best_oa_location":{"id":"pmh:oai:arXiv.org:1902.08171","is_oa":true,"landing_page_url":"http://arxiv.org/abs/1902.08171","pdf_url":"https://arxiv.org/pdf/1902.08171","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"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":"text"},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/17","display_name":"Partnerships for the goals","score":0.44999998807907104}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":33,"referenced_works":["https://openalex.org/W272277767","https://openalex.org/W1530431424","https://openalex.org/W1978224415","https://openalex.org/W1979559842","https://openalex.org/W2003753589","https://openalex.org/W2028781966","https://openalex.org/W2029213856","https://openalex.org/W2040073627","https://openalex.org/W2045983409","https://openalex.org/W2050507755","https://openalex.org/W2087445541","https://openalex.org/W2099641086","https://openalex.org/W2120580172","https://openalex.org/W2124252039","https://openalex.org/W2129131372","https://openalex.org/W2141159272","https://openalex.org/W2145962650","https://openalex.org/W2158121106","https://openalex.org/W2164098335","https://openalex.org/W2168955340","https://openalex.org/W2290632462","https://openalex.org/W2399506744","https://openalex.org/W2480981092","https://openalex.org/W2496323672","https://openalex.org/W2510601019","https://openalex.org/W2556237558","https://openalex.org/W3099514962","https://openalex.org/W3104624268","https://openalex.org/W3122732016","https://openalex.org/W4214613059","https://openalex.org/W6649031020","https://openalex.org/W6712781682","https://openalex.org/W6721875038"],"related_works":["https://openalex.org/W2099321050","https://openalex.org/W2890952311","https://openalex.org/W2509955295","https://openalex.org/W2047275718","https://openalex.org/W2034957211","https://openalex.org/W2890107589","https://openalex.org/W2388952560","https://openalex.org/W110819671","https://openalex.org/W2149282631","https://openalex.org/W2011611369"],"abstract_inverted_index":{"We":[0,32],"analyze":[1],"the":[2,47],"decomposition":[3],"of":[4,13,78],"a":[5,11,14,18,24,28,34,61],"data":[6],"matrix,":[7],"assumed":[8],"to":[9,60],"be":[10,51],"superposition":[12],"low-rank":[15],"component":[16,19],"and":[17,40,44,83],"which":[20],"is":[21],"sparse":[22],"in":[23,76,81],"known":[25],"dictionary,":[26],"using":[27],"convex":[29],"demixing":[30],"method.":[31],"provide":[33],"unified":[35],"analysis,":[36],"encompassing":[37],"both":[38],"undercomplete":[39],"overcomplete":[41],"dictionary":[42,87],"cases,":[43],"show":[45],"that":[46],"constituent":[48],"components":[49],"can":[50],"successfully":[52],"recovered":[53],"under":[54],"some":[55],"relatively":[56],"mild":[57],"assumptions":[58],"up":[59],"certain":[62],"global":[63],"sparsity":[64,84],"level.":[65],"Further,":[66],"we":[67],"corroborate":[68],"our":[69],"theoretical":[70],"results":[71],"by":[72],"presenting":[73],"empirical":[74],"evaluations":[75],"terms":[77],"phase":[79],"transitions":[80],"rank":[82],"for":[85],"various":[86],"sizes.":[88]},"counts_by_year":[{"year":2021,"cited_by_count":1},{"year":2020,"cited_by_count":1},{"year":2019,"cited_by_count":1},{"year":2018,"cited_by_count":1},{"year":2017,"cited_by_count":2},{"year":2016,"cited_by_count":1}],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-10-10T00:00:00"}