{"id":"https://openalex.org/W2939058456","doi":"https://doi.org/10.1109/icassp.2019.8683095","title":"Fast and Communication-efficient Distributed Pca","display_name":"Fast and Communication-efficient Distributed Pca","publication_year":2019,"publication_date":"2019-04-17","ids":{"openalex":"https://openalex.org/W2939058456","doi":"https://doi.org/10.1109/icassp.2019.8683095","mag":"2939058456"},"language":"en","primary_location":{"id":"doi:10.1109/icassp.2019.8683095","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icassp.2019.8683095","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ICASSP 2019 - 2019 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)","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/A5011938642","display_name":"Arpita Gang","orcid":"https://orcid.org/0000-0003-3825-130X"},"institutions":[{"id":"https://openalex.org/I102322142","display_name":"Rutgers, The State University of New Jersey","ror":"https://ror.org/05vt9qd57","country_code":"US","type":"education","lineage":["https://openalex.org/I102322142"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Arpita Gang","raw_affiliation_strings":["Dept. of Electrical and Computer Engineering, Rutgers University, New Brunswick, NJ, USA"],"affiliations":[{"raw_affiliation_string":"Dept. of Electrical and Computer Engineering, Rutgers University, New Brunswick, NJ, USA","institution_ids":["https://openalex.org/I102322142"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5058429805","display_name":"Haroon Raja","orcid":null},"institutions":[{"id":"https://openalex.org/I102322142","display_name":"Rutgers, The State University of New Jersey","ror":"https://ror.org/05vt9qd57","country_code":"US","type":"education","lineage":["https://openalex.org/I102322142"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Haroon Raja","raw_affiliation_strings":["Dept. of Electrical and Computer Engineering, Rutgers University, New Brunswick, NJ, USA"],"affiliations":[{"raw_affiliation_string":"Dept. of Electrical and Computer Engineering, Rutgers University, New Brunswick, NJ, USA","institution_ids":["https://openalex.org/I102322142"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5028718006","display_name":"Waheed U. Bajwa","orcid":"https://orcid.org/0000-0003-4406-5263"},"institutions":[{"id":"https://openalex.org/I102322142","display_name":"Rutgers, The State University of New Jersey","ror":"https://ror.org/05vt9qd57","country_code":"US","type":"education","lineage":["https://openalex.org/I102322142"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Waheed U. Bajwa","raw_affiliation_strings":["Dept. of Electrical and Computer Engineering, Rutgers University, New Brunswick, NJ, USA"],"affiliations":[{"raw_affiliation_string":"Dept. of Electrical and Computer Engineering, Rutgers University, New Brunswick, NJ, USA","institution_ids":["https://openalex.org/I102322142"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5011938642"],"corresponding_institution_ids":["https://openalex.org/I102322142"],"apc_list":null,"apc_paid":null,"fwci":3.0267,"has_fulltext":false,"cited_by_count":22,"citation_normalized_percentile":{"value":0.91756181,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":90,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"7450","last_page":"7454"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10500","display_name":"Sparse and Compressive Sensing Techniques","score":0.9995999932289124,"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":0.9995999932289124,"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":0.9994000196456909,"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":0.9979000091552734,"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/principal-component-analysis","display_name":"Principal component analysis","score":0.7999855279922485},{"id":"https://openalex.org/keywords/subspace-topology","display_name":"Subspace topology","score":0.7253971695899963},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7081546187400818},{"id":"https://openalex.org/keywords/convergence","display_name":"Convergence (economics)","score":0.6736960411071777},{"id":"https://openalex.org/keywords/principal","display_name":"Principal (computer security)","score":0.662109375},{"id":"https://openalex.org/keywords/massively-parallel","display_name":"Massively parallel","score":0.5428389310836792},{"id":"https://openalex.org/keywords/covariance-matrix","display_name":"Covariance matrix","score":0.5196036696434021},{"id":"https://openalex.org/keywords/overhead","display_name":"Overhead (engineering)","score":0.5026898384094238},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.44080305099487305},{"id":"https://openalex.org/keywords/covariance","display_name":"Covariance","score":0.41939738392829895},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.28568869829177856},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.20045188069343567},{"id":"https://openalex.org/keywords/parallel-computing","display_name":"Parallel computing","score":0.18640148639678955},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.09864309430122375}],"concepts":[{"id":"https://openalex.org/C27438332","wikidata":"https://www.wikidata.org/wiki/Q2873","display_name":"Principal component analysis","level":2,"score":0.7999855279922485},{"id":"https://openalex.org/C32834561","wikidata":"https://www.wikidata.org/wiki/Q660730","display_name":"Subspace topology","level":2,"score":0.7253971695899963},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7081546187400818},{"id":"https://openalex.org/C2777303404","wikidata":"https://www.wikidata.org/wiki/Q759757","display_name":"Convergence (economics)","level":2,"score":0.6736960411071777},{"id":"https://openalex.org/C144559511","wikidata":"https://www.wikidata.org/wiki/Q2986279","display_name":"Principal (computer security)","level":2,"score":0.662109375},{"id":"https://openalex.org/C190475519","wikidata":"https://www.wikidata.org/wiki/Q544384","display_name":"Massively parallel","level":2,"score":0.5428389310836792},{"id":"https://openalex.org/C185142706","wikidata":"https://www.wikidata.org/wiki/Q1134404","display_name":"Covariance matrix","level":2,"score":0.5196036696434021},{"id":"https://openalex.org/C2779960059","wikidata":"https://www.wikidata.org/wiki/Q7113681","display_name":"Overhead (engineering)","level":2,"score":0.5026898384094238},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.44080305099487305},{"id":"https://openalex.org/C178650346","wikidata":"https://www.wikidata.org/wiki/Q201984","display_name":"Covariance","level":2,"score":0.41939738392829895},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.28568869829177856},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.20045188069343567},{"id":"https://openalex.org/C173608175","wikidata":"https://www.wikidata.org/wiki/Q232661","display_name":"Parallel computing","level":1,"score":0.18640148639678955},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.09864309430122375},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0},{"id":"https://openalex.org/C50522688","wikidata":"https://www.wikidata.org/wiki/Q189833","display_name":"Economic growth","level":1,"score":0.0},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/icassp.2019.8683095","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icassp.2019.8683095","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ICASSP 2019 - 2019 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)","raw_type":"proceedings-article"},{"id":"pmh:oai:alma.01RUT_INST:11664804390004646","is_oa":false,"landing_page_url":"https://scholarship.libraries.rutgers.edu/esploro/outputs/conferenceProceeding/Fast-and-Communication-efficient-Distributed-Pca/991031664299704646","pdf_url":null,"source":{"id":"https://openalex.org/S4210197018","display_name":"View","issn_l":"2688-268X","issn":["2688-268X","2688-3988"],"is_oa":false,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310320595","host_organization_name":"Wiley","host_organization_lineage":["https://openalex.org/P4310320595"],"host_organization_lineage_names":["Wiley"],"type":"journal"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Conference Proceedings"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":48,"referenced_works":["https://openalex.org/W1571416372","https://openalex.org/W1616857247","https://openalex.org/W1923365686","https://openalex.org/W1954823950","https://openalex.org/W1981745143","https://openalex.org/W1988720110","https://openalex.org/W2020677486","https://openalex.org/W2023401026","https://openalex.org/W2044212084","https://openalex.org/W2068254488","https://openalex.org/W2074796812","https://openalex.org/W2095846217","https://openalex.org/W2097303721","https://openalex.org/W2121820607","https://openalex.org/W2130613472","https://openalex.org/W2131329059","https://openalex.org/W2142535750","https://openalex.org/W2152666411","https://openalex.org/W2161936690","https://openalex.org/W2166021275","https://openalex.org/W2279901945","https://openalex.org/W2289981213","https://openalex.org/W2291545909","https://openalex.org/W2295566694","https://openalex.org/W2723552999","https://openalex.org/W2733300693","https://openalex.org/W2788706426","https://openalex.org/W2792751837","https://openalex.org/W2891050651","https://openalex.org/W2936995161","https://openalex.org/W2963879412","https://openalex.org/W3099715789","https://openalex.org/W3124790153","https://openalex.org/W3137068445","https://openalex.org/W4250857377","https://openalex.org/W4289494416","https://openalex.org/W6655757316","https://openalex.org/W6682336573","https://openalex.org/W6684187592","https://openalex.org/W6684753248","https://openalex.org/W6696666249","https://openalex.org/W6740710678","https://openalex.org/W6748181190","https://openalex.org/W6754475447","https://openalex.org/W6761030284","https://openalex.org/W6763670057","https://openalex.org/W6792016399","https://openalex.org/W6999947317"],"related_works":["https://openalex.org/W1980381208","https://openalex.org/W1975632186","https://openalex.org/W3027745756","https://openalex.org/W3205213561","https://openalex.org/W2531880140","https://openalex.org/W2364594919","https://openalex.org/W2167092671","https://openalex.org/W2886934452","https://openalex.org/W1489099099","https://openalex.org/W2024369332"],"abstract_inverted_index":{"This":[0],"paper":[1,74],"focuses":[2],"on":[3],"principal":[4,12,120],"components":[5],"analysis":[6],"(PCA),":[7],"which":[8,34],"involves":[9],"estimating":[10],"the":[11,20,36,49,112,119,134],"subspace":[13,89],"of":[14,22,38,45,61,78,94,100,115],"a":[15,43,65,79],"data":[16],"covariance":[17],"matrix,":[18],"in":[19],"age":[21],"big":[23],"data.":[24],"Massively":[25],"large":[26],"datasets":[27],"often":[28],"require":[29],"storage":[30],"across":[31],"multiple":[32],"machines,":[33],"precludes":[35],"use":[37],"cen-tralized":[39],"PCA":[40,50,81],"solutions.":[41],"While":[42],"number":[44],"distributed":[46,80,84],"solutions":[47,63],"to":[48,118,129],"problem":[51],"have":[52,130],"been":[53],"proposed":[54],"recently,":[55],"convergence":[56,114,132],"guarantees":[57,108],"and/or":[58],"communications":[59,71],"overhead":[60],"these":[62],"remain":[64],"concern.":[66],"With":[67],"an":[68],"eye":[69],"towards":[70],"efficiency,":[72],"this":[73],"introduces":[75],"two":[76],"variants":[77,93],"algorithm":[82,86],"termed":[83],"Sanger's":[85],"(DSA).":[87],"Principal":[88],"estimation":[90],"using":[91],"both":[92],"DSA":[95,117],"is":[96,126],"communication":[97],"efficient":[98],"because":[99],"its":[101,123],"one":[102],"time-scale":[103],"nature.":[104],"In":[105],"addition,":[106],"theoretical":[107],"are":[109],"provided":[110],"for":[111],"asymptotic":[113],"basic":[116],"subspace,":[121],"while":[122],"\"accelerated\"":[124],"variant":[125],"numerically":[127],"shown":[128],"faster":[131],"than":[133],"state-of-the-art.":[135]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":2},{"year":2023,"cited_by_count":3},{"year":2022,"cited_by_count":4},{"year":2021,"cited_by_count":8},{"year":2020,"cited_by_count":3},{"year":2019,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}