{"id":"https://openalex.org/W2756182580","doi":"https://doi.org/10.1109/allerton.2017.8262819","title":"Finite sample guarantees for PCA in non-isotropic and data-dependent noise","display_name":"Finite sample guarantees for PCA in non-isotropic and data-dependent noise","publication_year":2017,"publication_date":"2017-10-01","ids":{"openalex":"https://openalex.org/W2756182580","doi":"https://doi.org/10.1109/allerton.2017.8262819","mag":"2756182580"},"language":"en","primary_location":{"id":"doi:10.1109/allerton.2017.8262819","is_oa":false,"landing_page_url":"https://doi.org/10.1109/allerton.2017.8262819","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2017 55th Annual Allerton Conference on Communication, Control, and Computing (Allerton)","raw_type":"proceedings-article"},"type":"preprint","indexed_in":["arxiv","crossref","datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/1709.06255","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5005043504","display_name":"Namrata Vaswani","orcid":"https://orcid.org/0000-0003-2774-0650"},"institutions":[{"id":"https://openalex.org/I173911158","display_name":"Iowa State University","ror":"https://ror.org/04rswrd78","country_code":"US","type":"education","lineage":["https://openalex.org/I173911158"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Namrata Vaswani","raw_affiliation_strings":["Department of Electrical and Computer Engineering, Iowa State University","Department of Electrical & Computer Engineering, Iowa State University;"],"affiliations":[{"raw_affiliation_string":"Department of Electrical and Computer Engineering, Iowa State University","institution_ids":["https://openalex.org/I173911158"]},{"raw_affiliation_string":"Department of Electrical & Computer Engineering, Iowa State University;","institution_ids":["https://openalex.org/I173911158"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5087330283","display_name":"Praneeth Narayanamurthy","orcid":"https://orcid.org/0000-0002-5761-7357"},"institutions":[{"id":"https://openalex.org/I173911158","display_name":"Iowa State University","ror":"https://ror.org/04rswrd78","country_code":"US","type":"education","lineage":["https://openalex.org/I173911158"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Praneeth Narayanamurthy","raw_affiliation_strings":["Department of Electrical and Computer Engineering, Iowa State University","Department of Electrical & Computer Engineering, Iowa State University;"],"affiliations":[{"raw_affiliation_string":"Department of Electrical and Computer Engineering, Iowa State University","institution_ids":["https://openalex.org/I173911158"]},{"raw_affiliation_string":"Department of Electrical & Computer Engineering, Iowa State University;","institution_ids":["https://openalex.org/I173911158"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5005043504"],"corresponding_institution_ids":["https://openalex.org/I173911158"],"apc_list":null,"apc_paid":null,"fwci":0.2466,"has_fulltext":true,"cited_by_count":1,"citation_normalized_percentile":{"value":0.5567544,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":94},"biblio":{"volume":null,"issue":null,"first_page":"783","last_page":"789"},"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":0.9998999834060669,"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/T10688","display_name":"Image and Signal Denoising Methods","score":0.9991999864578247,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"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/principal-component-analysis","display_name":"Principal component analysis","score":0.8273502588272095},{"id":"https://openalex.org/keywords/subspace-topology","display_name":"Subspace topology","score":0.799770712852478},{"id":"https://openalex.org/keywords/correctness","display_name":"Correctness","score":0.7414941787719727},{"id":"https://openalex.org/keywords/noise","display_name":"Noise (video)","score":0.7151311039924622},{"id":"https://openalex.org/keywords/sample","display_name":"Sample (material)","score":0.5946211218833923},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.5420920848846436},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5215585231781006},{"id":"https://openalex.org/keywords/isotropy","display_name":"Isotropy","score":0.5086191892623901},{"id":"https://openalex.org/keywords/missing-data","display_name":"Missing data","score":0.49448633193969727},{"id":"https://openalex.org/keywords/sample-complexity","display_name":"Sample complexity","score":0.4671719968318939},{"id":"https://openalex.org/keywords/constant","display_name":"Constant (computer programming)","score":0.4462760090827942},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.3842460811138153},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.354392945766449},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.2956348657608032},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.12922340631484985},{"id":"https://openalex.org/keywords/physics","display_name":"Physics","score":0.06434264779090881}],"concepts":[{"id":"https://openalex.org/C27438332","wikidata":"https://www.wikidata.org/wiki/Q2873","display_name":"Principal component analysis","level":2,"score":0.8273502588272095},{"id":"https://openalex.org/C32834561","wikidata":"https://www.wikidata.org/wiki/Q660730","display_name":"Subspace topology","level":2,"score":0.799770712852478},{"id":"https://openalex.org/C55439883","wikidata":"https://www.wikidata.org/wiki/Q360812","display_name":"Correctness","level":2,"score":0.7414941787719727},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.7151311039924622},{"id":"https://openalex.org/C198531522","wikidata":"https://www.wikidata.org/wiki/Q485146","display_name":"Sample (material)","level":2,"score":0.5946211218833923},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.5420920848846436},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5215585231781006},{"id":"https://openalex.org/C184050105","wikidata":"https://www.wikidata.org/wiki/Q273163","display_name":"Isotropy","level":2,"score":0.5086191892623901},{"id":"https://openalex.org/C9357733","wikidata":"https://www.wikidata.org/wiki/Q6878417","display_name":"Missing data","level":2,"score":0.49448633193969727},{"id":"https://openalex.org/C2778445095","wikidata":"https://www.wikidata.org/wiki/Q18354077","display_name":"Sample complexity","level":2,"score":0.4671719968318939},{"id":"https://openalex.org/C2777027219","wikidata":"https://www.wikidata.org/wiki/Q1284190","display_name":"Constant (computer programming)","level":2,"score":0.4462760090827942},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.3842460811138153},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.354392945766449},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.2956348657608032},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.12922340631484985},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.06434264779090881},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"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/C97355855","wikidata":"https://www.wikidata.org/wiki/Q11473","display_name":"Thermodynamics","level":1,"score":0.0},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0}],"mesh":[],"locations_count":4,"locations":[{"id":"doi:10.1109/allerton.2017.8262819","is_oa":false,"landing_page_url":"https://doi.org/10.1109/allerton.2017.8262819","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2017 55th Annual Allerton Conference on Communication, Control, and Computing (Allerton)","raw_type":"proceedings-article"},{"id":"pmh:oai:arXiv.org:1709.06255","is_oa":true,"landing_page_url":"http://arxiv.org/abs/1709.06255","pdf_url":"https://arxiv.org/pdf/1709.06255","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"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"},{"id":"mag:2756182580","is_oa":true,"landing_page_url":"https://arxiv.org/pdf/1709.06255.pdf","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"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":"arXiv (Cornell University)","raw_type":null},{"id":"doi:10.48550/arxiv.1709.06255","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.1709.06255","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"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":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"article"}],"best_oa_location":{"id":"pmh:oai:arXiv.org:1709.06255","is_oa":true,"landing_page_url":"http://arxiv.org/abs/1709.06255","pdf_url":"https://arxiv.org/pdf/1709.06255","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"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":[{"display_name":"Peace, Justice and strong institutions","score":0.6399999856948853,"id":"https://metadata.un.org/sdg/16"}],"awards":[],"funders":[],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W2756182580.pdf","grobid_xml":"https://content.openalex.org/works/W2756182580.grobid-xml"},"referenced_works_count":26,"referenced_works":["https://openalex.org/W1520752838","https://openalex.org/W1970377488","https://openalex.org/W1975189025","https://openalex.org/W1995168330","https://openalex.org/W2015418199","https://openalex.org/W2057197276","https://openalex.org/W2094644779","https://openalex.org/W2099781564","https://openalex.org/W2106005123","https://openalex.org/W2107411554","https://openalex.org/W2137798267","https://openalex.org/W2142224912","https://openalex.org/W2145962650","https://openalex.org/W2403076655","https://openalex.org/W2467768057","https://openalex.org/W2516614812","https://openalex.org/W2530948029","https://openalex.org/W2951713178","https://openalex.org/W2963443408","https://openalex.org/W2964167320","https://openalex.org/W2965497096","https://openalex.org/W3098045837","https://openalex.org/W3105364218","https://openalex.org/W6681872947","https://openalex.org/W6693777606","https://openalex.org/W6695768178"],"related_works":["https://openalex.org/W3034703585","https://openalex.org/W1588030230","https://openalex.org/W3098460717","https://openalex.org/W2773706250","https://openalex.org/W2781141869","https://openalex.org/W2593349530","https://openalex.org/W2618684440","https://openalex.org/W2885344524","https://openalex.org/W1501972811","https://openalex.org/W37129894","https://openalex.org/W2166581276","https://openalex.org/W3119133192","https://openalex.org/W2914080577","https://openalex.org/W2166107678","https://openalex.org/W2267569616","https://openalex.org/W2970605810","https://openalex.org/W2982696156","https://openalex.org/W2950161005","https://openalex.org/W2999701484","https://openalex.org/W2191788215"],"abstract_inverted_index":{"This":[0],"work":[1,48,59],"obtains":[2],"novel":[3],"finite":[4],"sample":[5,79],"guarantees":[6],"for":[7],"Principal":[8],"Component":[9],"Analysis":[10],"(PCA).":[11],"These":[12],"hold":[13],"even":[14],"when":[15],"the":[16,32,36,39,68,78,93,100],"corrupting":[17],"noise":[18,37,94],"is":[19,28,88,96],"non-isotropic,":[20],"and":[21,38],"a":[22,50,89],"part":[23],"(or":[24],"all":[25],"of":[26,31,92,102],"it)":[27],"data-dependent.":[29],"Because":[30],"latter,":[33],"in":[34,46,56,71],"general,":[35],"true":[40],"data":[41],"are":[42,49],"correlated.":[43],"The":[44],"results":[45,75],"this":[47,61,72],"significant":[51],"improvement":[52],"over":[53],"those":[54],"given":[55],"our":[57,74,103],"earlier":[58],"where":[60],"\u201ccorrelated-PCA\u201d":[62],"problem":[63],"was":[64],"first":[65],"studied.":[66],"In":[67],"regime":[69],"analyzed":[70],"work,":[73],"imply":[76],"that":[77,87],"complexity":[80],"required":[81],"to":[82],"achieve":[83],"subspace":[84],"recovery":[85],"error":[86],"constant":[90],"fraction":[91],"level":[95],"near-optimal.":[97],"We":[98],"demonstrate":[99],"validity":[101],"analysis":[104],"through":[105],"numerical":[106],"experiments.":[107]},"counts_by_year":[{"year":2019,"cited_by_count":1}],"updated_date":"2026-03-20T23:20:44.827607","created_date":"2025-10-10T00:00:00"}