{"id":"https://openalex.org/W2981687470","doi":"https://doi.org/10.1109/jstsp.2021.3056918","title":"Prema: Principled Tensor Data Recovery From Multiple Aggregated Views","display_name":"Prema: Principled Tensor Data Recovery From Multiple Aggregated Views","publication_year":2021,"publication_date":"2021-02-03","ids":{"openalex":"https://openalex.org/W2981687470","doi":"https://doi.org/10.1109/jstsp.2021.3056918","mag":"2981687470"},"language":"en","primary_location":{"id":"doi:10.1109/jstsp.2021.3056918","is_oa":false,"landing_page_url":"https://doi.org/10.1109/jstsp.2021.3056918","pdf_url":null,"source":{"id":"https://openalex.org/S42167783","display_name":"IEEE Journal of Selected Topics in Signal Processing","issn_l":"1932-4553","issn":["1932-4553","1941-0484"],"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 Journal of Selected Topics in Signal Processing","raw_type":"journal-article"},"type":"preprint","indexed_in":["arxiv","crossref","datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/1910.12001","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5113372873","display_name":"Faisal M. Almutairi","orcid":null},"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"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Faisal M. Almutairi","raw_affiliation_strings":["Department of Electrical and Computer Engineering, University of Minnesota, Minneapolis, MN, USA","[Dept. of Electrical and Computer Engineering, University of Minnesota, Minneapolis, MN, USA]"],"affiliations":[{"raw_affiliation_string":"Department of Electrical and Computer Engineering, University of Minnesota, Minneapolis, MN, USA","institution_ids":["https://openalex.org/I130238516"]},{"raw_affiliation_string":"[Dept. of Electrical and Computer Engineering, University of Minnesota, Minneapolis, MN, USA]","institution_ids":["https://openalex.org/I130238516"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5034936665","display_name":"Charilaos I. Kanatsoulis","orcid":"https://orcid.org/0000-0002-0952-1561"},"institutions":[{"id":"https://openalex.org/I2800403580","display_name":"University of Minnesota System","ror":"https://ror.org/03grvy078","country_code":"US","type":"education","lineage":["https://openalex.org/I2800403580"]},{"id":"https://openalex.org/I79576946","display_name":"University of Pennsylvania","ror":"https://ror.org/00b30xv10","country_code":"US","type":"education","lineage":["https://openalex.org/I79576946"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Charilaos I. Kanatsoulis","raw_affiliation_strings":["Department of Electrical and Systems Engineering, University of Pennsylvania, Philadelphia, PA, USA","university of minnesota;"],"affiliations":[{"raw_affiliation_string":"Department of Electrical and Systems Engineering, University of Pennsylvania, Philadelphia, PA, USA","institution_ids":["https://openalex.org/I79576946"]},{"raw_affiliation_string":"university of minnesota;","institution_ids":["https://openalex.org/I2800403580"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5050186120","display_name":"Nicholas D. Sidiropoulos","orcid":"https://orcid.org/0000-0002-3385-7911"},"institutions":[{"id":"https://openalex.org/I51556381","display_name":"University of Virginia","ror":"https://ror.org/0153tk833","country_code":"US","type":"education","lineage":["https://openalex.org/I51556381"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Nicholas D. Sidiropoulos","raw_affiliation_strings":["Department of Electrical and Computer Engineering, University of Virginia, Charlottesville, VA, USA","Department of Electrical and Computer Engineering , University of Virginia, Charlottesville, VA, USA"],"affiliations":[{"raw_affiliation_string":"Department of Electrical and Computer Engineering, University of Virginia, Charlottesville, VA, USA","institution_ids":["https://openalex.org/I51556381"]},{"raw_affiliation_string":"Department of Electrical and Computer Engineering , University of Virginia, Charlottesville, VA, USA","institution_ids":["https://openalex.org/I51556381"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5113372873"],"corresponding_institution_ids":["https://openalex.org/I130238516"],"apc_list":null,"apc_paid":null,"fwci":0.138,"has_fulltext":false,"cited_by_count":3,"citation_normalized_percentile":{"value":0.29314421,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":96},"biblio":{"volume":"15","issue":"3","first_page":"535","last_page":"549"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12303","display_name":"Tensor decomposition and applications","score":0.9998000264167786,"subfield":{"id":"https://openalex.org/subfields/2605","display_name":"Computational Mathematics"},"field":{"id":"https://openalex.org/fields/26","display_name":"Mathematics"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T12303","display_name":"Tensor decomposition and applications","score":0.9998000264167786,"subfield":{"id":"https://openalex.org/subfields/2605","display_name":"Computational Mathematics"},"field":{"id":"https://openalex.org/fields/26","display_name":"Mathematics"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10901","display_name":"Advanced Data Compression Techniques","score":0.9793000221252441,"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"}},{"id":"https://openalex.org/T10500","display_name":"Sparse and Compressive Sensing Techniques","score":0.9736999869346619,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7091031074523926},{"id":"https://openalex.org/keywords/rank","display_name":"Rank (graph theory)","score":0.6059094667434692},{"id":"https://openalex.org/keywords/tensor","display_name":"Tensor (intrinsic definition)","score":0.5520409345626831},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.5355401635169983},{"id":"https://openalex.org/keywords/data-aggregator","display_name":"Data aggregator","score":0.5134130716323853},{"id":"https://openalex.org/keywords/scale","display_name":"Scale (ratio)","score":0.42919033765792847},{"id":"https://openalex.org/keywords/data-science","display_name":"Data science","score":0.3832976818084717},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.37655821442604065},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.33881765604019165},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.13140428066253662},{"id":"https://openalex.org/keywords/geography","display_name":"Geography","score":0.12069109082221985},{"id":"https://openalex.org/keywords/cartography","display_name":"Cartography","score":0.09185367822647095}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7091031074523926},{"id":"https://openalex.org/C164226766","wikidata":"https://www.wikidata.org/wiki/Q7293202","display_name":"Rank (graph theory)","level":2,"score":0.6059094667434692},{"id":"https://openalex.org/C155281189","wikidata":"https://www.wikidata.org/wiki/Q3518150","display_name":"Tensor (intrinsic definition)","level":2,"score":0.5520409345626831},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.5355401635169983},{"id":"https://openalex.org/C82578977","wikidata":"https://www.wikidata.org/wiki/Q16773055","display_name":"Data aggregator","level":3,"score":0.5134130716323853},{"id":"https://openalex.org/C2778755073","wikidata":"https://www.wikidata.org/wiki/Q10858537","display_name":"Scale (ratio)","level":2,"score":0.42919033765792847},{"id":"https://openalex.org/C2522767166","wikidata":"https://www.wikidata.org/wiki/Q2374463","display_name":"Data science","level":1,"score":0.3832976818084717},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.37655821442604065},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.33881765604019165},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.13140428066253662},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.12069109082221985},{"id":"https://openalex.org/C58640448","wikidata":"https://www.wikidata.org/wiki/Q42515","display_name":"Cartography","level":1,"score":0.09185367822647095},{"id":"https://openalex.org/C202444582","wikidata":"https://www.wikidata.org/wiki/Q837863","display_name":"Pure mathematics","level":1,"score":0.0},{"id":"https://openalex.org/C31258907","wikidata":"https://www.wikidata.org/wiki/Q1301371","display_name":"Computer network","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},{"id":"https://openalex.org/C24590314","wikidata":"https://www.wikidata.org/wiki/Q336038","display_name":"Wireless sensor network","level":2,"score":0.0}],"mesh":[],"locations_count":4,"locations":[{"id":"doi:10.1109/jstsp.2021.3056918","is_oa":false,"landing_page_url":"https://doi.org/10.1109/jstsp.2021.3056918","pdf_url":null,"source":{"id":"https://openalex.org/S42167783","display_name":"IEEE Journal of Selected Topics in Signal Processing","issn_l":"1932-4553","issn":["1932-4553","1941-0484"],"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 Journal of Selected Topics in Signal Processing","raw_type":"journal-article"},{"id":"pmh:oai:arXiv.org:1910.12001","is_oa":true,"landing_page_url":"http://arxiv.org/abs/1910.12001","pdf_url":"https://arxiv.org/pdf/1910.12001","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":"","raw_type":null},{"id":"mag:2981687470","is_oa":true,"landing_page_url":"https://arxiv.org/pdf/1910.12001v2","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.1910.12001","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.1910.12001","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:1910.12001","is_oa":true,"landing_page_url":"http://arxiv.org/abs/1910.12001","pdf_url":"https://arxiv.org/pdf/1910.12001","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":"","raw_type":null},"sustainable_development_goals":[{"score":0.8199999928474426,"id":"https://metadata.un.org/sdg/16","display_name":"Peace, Justice and strong institutions"}],"awards":[{"id":"https://openalex.org/G3045547944","display_name":null,"funder_award_id":"NSF ECCS-1852831","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"},{"id":"https://openalex.org/G4904170738","display_name":null,"funder_award_id":"NSF IIS-1704074","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"},{"id":"https://openalex.org/G5948400979","display_name":null,"funder_award_id":"NSF ECCS-1608961","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"}],"funders":[{"id":"https://openalex.org/F4320306076","display_name":"National Science Foundation","ror":"https://ror.org/021nxhr62"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":49,"referenced_works":["https://openalex.org/W1636728768","https://openalex.org/W1966679176","https://openalex.org/W1970195563","https://openalex.org/W1986428488","https://openalex.org/W1990231296","https://openalex.org/W1992673035","https://openalex.org/W1993281116","https://openalex.org/W2000077104","https://openalex.org/W2012657629","https://openalex.org/W2021046129","https://openalex.org/W2024165284","https://openalex.org/W2035503723","https://openalex.org/W2036517815","https://openalex.org/W2042136148","https://openalex.org/W2051576420","https://openalex.org/W2057113224","https://openalex.org/W2075680224","https://openalex.org/W2093908039","https://openalex.org/W2110411158","https://openalex.org/W2150346598","https://openalex.org/W2158601794","https://openalex.org/W2171771747","https://openalex.org/W2172028276","https://openalex.org/W2258054274","https://openalex.org/W2268140711","https://openalex.org/W2469230926","https://openalex.org/W2528907418","https://openalex.org/W2552480641","https://openalex.org/W2567289326","https://openalex.org/W2623244766","https://openalex.org/W2775387120","https://openalex.org/W2798016471","https://openalex.org/W2888945818","https://openalex.org/W2890206502","https://openalex.org/W2890244317","https://openalex.org/W2938089538","https://openalex.org/W2965565138","https://openalex.org/W2989504803","https://openalex.org/W3010845201","https://openalex.org/W3023205342","https://openalex.org/W3121151732","https://openalex.org/W3122544757","https://openalex.org/W3145701640","https://openalex.org/W4230046490","https://openalex.org/W4242714621","https://openalex.org/W6684915226","https://openalex.org/W6693725088","https://openalex.org/W6729542563","https://openalex.org/W6736425207"],"related_works":["https://openalex.org/W3127919891","https://openalex.org/W3023205342","https://openalex.org/W2609340118","https://openalex.org/W2836524907","https://openalex.org/W2585384350","https://openalex.org/W1577119941","https://openalex.org/W2561274250","https://openalex.org/W3156643091","https://openalex.org/W3178557578","https://openalex.org/W2593434621","https://openalex.org/W3130423234","https://openalex.org/W2498507937","https://openalex.org/W2612584051","https://openalex.org/W1977368099","https://openalex.org/W2776588445","https://openalex.org/W3124297202","https://openalex.org/W2783391070","https://openalex.org/W2516795883","https://openalex.org/W2596669114","https://openalex.org/W3097707563"],"abstract_inverted_index":{"Multidimensional":[0],"data":[1,18,54,82,91,98,117,194],"have":[2,35],"become":[3],"ubiquitous":[4],"and":[5,70,84,95,143,164,202],"are":[6,55,101],"frequently":[7],"encountered":[8],"in":[9,47,105],"situations":[10],"where":[11],"the":[12,42,140,171,183,187],"information":[13],"is":[14,113],"aggregated":[15,39,46,68,122],"over":[16,24,71,123],"multiple":[17,38,119,141],"atoms.":[19],"The":[20,108,128],"aggregation":[21,172],"can":[22,66,151],"be":[23,67],"time":[25],"or":[26,49,57,79,158],"other":[27],"features,":[28],"such":[29,155],"as":[30,156],"geographical":[31],"location.":[32],"We":[33],"often":[34],"access":[36],"to":[37,114,138],"views":[40,142],"of":[41,73,110,170,177,185],"same":[43],"data,":[44,161],"each":[45],"one":[48],"more":[50],"dimensions,":[51],"especially":[52],"when":[53],"collected":[56],"measured":[58],"by":[59],"different":[60,124,196],"agencies.":[61],"For":[62],"instance,":[63],"item":[64],"sales":[65],"temporally,":[69],"groups":[72],"stores":[74],"based":[75],"on":[76],"their":[77],"location":[78],"affiliation.":[80],"However,":[81],"mining":[83],"machine":[85],"learning":[86],"models":[87],"benefit":[88],"from":[89,118,195],"detailed":[90],"for":[92],"personalized":[93],"analysis":[94],"prediction.":[96],"Thus,":[97],"disaggregation":[99,167],"algorithms":[100],"becoming":[102],"increasingly":[103],"important":[104],"various":[106],"domains.":[107],"goal":[109],"this":[111],"paper":[112,188],"reconstruct":[115],"finer-scale":[116],"coarse":[120],"views,":[121],"(subsets":[125],"of)":[126],"dimensions.":[127],"proposed":[129],"method,":[130],"called":[131,179],"Prema,":[132,186],"leverages":[133],"low-rank":[134],"tensor":[135],"factorization":[136],"tools":[137],"fuse":[139],"provide":[144],"recovery":[145],"guarantees":[146],"under":[147],"certain":[148],"conditions.":[149],"Prema":[150,178],"tackle":[152],"challenging":[153],"scenarios,":[154],"missing":[157],"partially":[159],"observed":[160],"double":[162],"aggregation,":[163],"even":[165],"blind":[166],"(without":[168],"knowledge":[169],"patterns)":[173],"using":[174,192],"a":[175],"variant":[176],"B-Prema.":[180],"To":[181],"showcase":[182],"effectiveness":[184],"includes":[189],"extensive":[190],"experiments":[191],"real":[193],"domains:":[197],"retail":[198],"sales,":[199],"crime":[200],"counts,":[201],"weather":[203],"observations.":[204]},"counts_by_year":[{"year":2021,"cited_by_count":1},{"year":2020,"cited_by_count":2}],"updated_date":"2026-04-09T08:11:56.329763","created_date":"2025-10-10T00:00:00"}
