{"id":"https://openalex.org/W4406265272","doi":"https://doi.org/10.1109/icspcc62635.2024.10770371","title":"Fast Low-Rank Approximation of Matrices via Randomization with Application to Tensor Completion","display_name":"Fast Low-Rank Approximation of Matrices via Randomization with Application to Tensor Completion","publication_year":2024,"publication_date":"2024-08-19","ids":{"openalex":"https://openalex.org/W4406265272","doi":"https://doi.org/10.1109/icspcc62635.2024.10770371"},"language":"en","primary_location":{"id":"doi:10.1109/icspcc62635.2024.10770371","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icspcc62635.2024.10770371","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 IEEE International Conference on Signal Processing, Communications and Computing (ICSPCC)","raw_type":"proceedings-article"},"type":"conference-paper","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/A5068640565","display_name":"M. F. Kaloorazi","orcid":null},"institutions":[{"id":"https://openalex.org/I181903023","display_name":"Xi'an Shiyou University","ror":"https://ror.org/040c7js64","country_code":"CN","type":"education","lineage":["https://openalex.org/I181903023"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"M. F. Kaloorazi","raw_affiliation_strings":["School of Electronic Engineering, Xi&#x0027;an Shiyou University,Xi&#x0027;an,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Electronic Engineering, Xi&#x0027;an Shiyou University,Xi&#x0027;an,China","institution_ids":["https://openalex.org/I181903023"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5070748575","display_name":"Salman Ahmadi\u2010Asl","orcid":"https://orcid.org/0000-0002-2614-0146"},"institutions":[{"id":"https://openalex.org/I4210116741","display_name":"Innopolis University","ror":"https://ror.org/02b7jh107","country_code":"RU","type":"education","lineage":["https://openalex.org/I4210116741"]}],"countries":["RU"],"is_corresponding":false,"raw_author_name":"S. Ahmadi-Asl","raw_affiliation_strings":["Innopolis University,MlKr Lab,Innopolis,Russia"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Innopolis University,MlKr Lab,Innopolis,Russia","institution_ids":["https://openalex.org/I4210116741"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100333004","display_name":"Jie Chen","orcid":"https://orcid.org/0000-0003-2306-8860"},"institutions":[{"id":"https://openalex.org/I17145004","display_name":"Northwestern Polytechnical University","ror":"https://ror.org/01y0j0j86","country_code":"CN","type":"education","lineage":["https://openalex.org/I17145004"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"J. Chen","raw_affiliation_strings":["CIAIC, Northwestern Polytechnical University,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"CIAIC, Northwestern Polytechnical University,China","institution_ids":["https://openalex.org/I17145004"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5054558832","display_name":"Susanto Rahardja","orcid":"https://orcid.org/0000-0003-0831-6934"},"institutions":[{"id":"https://openalex.org/I168639165","display_name":"Singapore Institute of Technology","ror":"https://ror.org/01v2c2791","country_code":"SG","type":"education","lineage":["https://openalex.org/I168639165"]}],"countries":["SG"],"is_corresponding":false,"raw_author_name":"S. Rahardja","raw_affiliation_strings":["Singapore Institute of Technology,Engineering Cluster"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Singapore Institute of Technology,Engineering Cluster","institution_ids":["https://openalex.org/I168639165"]}]}],"institutions":[],"countries_distinct_count":3,"institutions_distinct_count":4,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"5"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12303","display_name":"Tensor decomposition and applications","score":0.996999979019165,"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":0.996999979019165,"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/T11447","display_name":"Blind Source Separation Techniques","score":0.9933000206947327,"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/T10792","display_name":"Matrix Theory and Algorithms","score":0.9739000201225281,"subfield":{"id":"https://openalex.org/subfields/1703","display_name":"Computational Theory and Mathematics"},"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/randomization","display_name":"Randomization","score":0.698718249797821},{"id":"https://openalex.org/keywords/tensor","display_name":"Tensor (intrinsic definition)","score":0.5880553722381592},{"id":"https://openalex.org/keywords/low-rank-approximation","display_name":"Low-rank approximation","score":0.5696539282798767},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.4852564334869385},{"id":"https://openalex.org/keywords/matrix-completion","display_name":"Matrix completion","score":0.4774661362171173},{"id":"https://openalex.org/keywords/rank","display_name":"Rank (graph theory)","score":0.4318860173225403},{"id":"https://openalex.org/keywords/completion","display_name":"Completion (oil and gas wells)","score":0.42895159125328064},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.34219256043434143},{"id":"https://openalex.org/keywords/combinatorics","display_name":"Combinatorics","score":0.24659356474876404},{"id":"https://openalex.org/keywords/randomized-controlled-trial","display_name":"Randomized controlled trial","score":0.19747665524482727},{"id":"https://openalex.org/keywords/medicine","display_name":"Medicine","score":0.1613234579563141},{"id":"https://openalex.org/keywords/physics","display_name":"Physics","score":0.10513150691986084},{"id":"https://openalex.org/keywords/pure-mathematics","display_name":"Pure mathematics","score":0.09272751212120056}],"concepts":[{"id":"https://openalex.org/C204243189","wikidata":"https://www.wikidata.org/wiki/Q1363085","display_name":"Randomization","level":3,"score":0.698718249797821},{"id":"https://openalex.org/C155281189","wikidata":"https://www.wikidata.org/wiki/Q3518150","display_name":"Tensor (intrinsic definition)","level":2,"score":0.5880553722381592},{"id":"https://openalex.org/C90199385","wikidata":"https://www.wikidata.org/wiki/Q6692777","display_name":"Low-rank approximation","level":3,"score":0.5696539282798767},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.4852564334869385},{"id":"https://openalex.org/C2778459887","wikidata":"https://www.wikidata.org/wiki/Q6787865","display_name":"Matrix completion","level":3,"score":0.4774661362171173},{"id":"https://openalex.org/C164226766","wikidata":"https://www.wikidata.org/wiki/Q7293202","display_name":"Rank (graph theory)","level":2,"score":0.4318860173225403},{"id":"https://openalex.org/C2779538338","wikidata":"https://www.wikidata.org/wiki/Q2990590","display_name":"Completion (oil and gas wells)","level":2,"score":0.42895159125328064},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.34219256043434143},{"id":"https://openalex.org/C114614502","wikidata":"https://www.wikidata.org/wiki/Q76592","display_name":"Combinatorics","level":1,"score":0.24659356474876404},{"id":"https://openalex.org/C168563851","wikidata":"https://www.wikidata.org/wiki/Q1436668","display_name":"Randomized controlled trial","level":2,"score":0.19747665524482727},{"id":"https://openalex.org/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"score":0.1613234579563141},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.10513150691986084},{"id":"https://openalex.org/C202444582","wikidata":"https://www.wikidata.org/wiki/Q837863","display_name":"Pure mathematics","level":1,"score":0.09272751212120056},{"id":"https://openalex.org/C46141821","wikidata":"https://www.wikidata.org/wiki/Q209402","display_name":"Nuclear magnetic resonance","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/C141071460","wikidata":"https://www.wikidata.org/wiki/Q40821","display_name":"Surgery","level":1,"score":0.0},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icspcc62635.2024.10770371","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icspcc62635.2024.10770371","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 IEEE International Conference on Signal Processing, Communications and Computing (ICSPCC)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G1866958129","display_name":null,"funder_award_id":"103/134010028","funder_id":"https://openalex.org/F4320327407","funder_display_name":"Xi'an Shiyou University"}],"funders":[{"id":"https://openalex.org/F4320327407","display_name":"Xi'an Shiyou University","ror":null}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":["https://openalex.org/W2952489973","https://openalex.org/W4300776969","https://openalex.org/W2106005123","https://openalex.org/W2962884438","https://openalex.org/W2266965707","https://openalex.org/W4387323768","https://openalex.org/W2084983808","https://openalex.org/W4318564253","https://openalex.org/W2994409951","https://openalex.org/W2906317811"],"abstract_inverted_index":{"The":[0],"approximation":[1,61],"of":[2,12,89,105,137],"voluminous":[3],"datasets,":[4],"which":[5,69],"admit":[6],"a":[7,52,90],"low-rank":[8,59,123],"structure,":[9],"by":[10],"ones":[11],"considerably":[13],"lower":[14],"ranks":[15],"have":[16,28,70],"recently":[17],"found":[18],"many":[19],"practical":[20],"applications":[21],"in":[22,41,44],"science":[23],"and":[24,38,62,84,140],"engineering.":[25],"Randomized":[26],"algorithms":[27,74,133],"emerged":[29],"as":[30,76],"an":[31,118],"powerful":[32],"choice,":[33],"due":[34],"to":[35,93,116,134],"their":[36],"efficacy":[37],"efficiency,":[39],"particularly":[40],"exploiting":[42],"parallelism":[43],"modern":[45],"architectures.":[46],"In":[47,109],"this":[48],"paper,":[49],"we":[50,86,111],"present":[51],"fast":[53],"randomized":[54,91],"rank-revealing":[55,103],"algorithm":[56,92,115,120],"tailored":[57],"for":[58,101,121],"matrix":[60],"decomposition.":[63],"However,":[64],"unlike":[65],"the":[66,77,95,102,106,122,127],"previous":[67],"works,":[68],"applied":[71],"deterministic":[72],"decompositional":[73],"such":[75],"singular":[78],"value":[79],"decomposition":[80],"(SVD),":[81],"pivoted":[82],"QR":[83],"QLP,":[85],"make":[87],"use":[88],"factorize":[94],"compressed":[96],"matrix.":[97],"We":[98,129],"furnish":[99],"bounds":[100],"property":[104],"proposed":[107,114,132],"algorithm.":[108],"addition,":[110],"utilize":[112],"our":[113,131],"develop":[117],"efficient":[119],"tensor":[124],"decomposition,":[125],"namely":[126],"tensor-SVD.":[128],"apply":[130],"various":[135],"classes":[136],"multidimensional":[138],"synthetic":[139],"real-world":[141],"datasets.":[142]},"counts_by_year":[],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}
