{"id":"https://openalex.org/W3081460781","doi":"https://doi.org/10.1137/20m136205x","title":"Column $\\ell_{2,0}$-Norm Regularized Factorization Model of Low-Rank Matrix Recovery and Its Computation","display_name":"Column $\\ell_{2,0}$-Norm Regularized Factorization Model of Low-Rank Matrix Recovery and Its Computation","publication_year":2022,"publication_date":"2022-05-19","ids":{"openalex":"https://openalex.org/W3081460781","doi":"https://doi.org/10.1137/20m136205x","mag":"3081460781"},"language":"en","primary_location":{"id":"doi:10.1137/20m136205x","is_oa":false,"landing_page_url":"https://doi.org/10.1137/20m136205x","pdf_url":null,"source":{"id":"https://openalex.org/S928796702","display_name":"SIAM Journal on Optimization","issn_l":"1052-6234","issn":["1052-6234","1095-7189"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320508","host_organization_name":"Society for Industrial and Applied Mathematics","host_organization_lineage":["https://openalex.org/P4310320508"],"host_organization_lineage_names":["Society for Industrial and Applied Mathematics"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"SIAM Journal on Optimization","raw_type":"journal-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/A5054128611","display_name":"Ting Tao","orcid":null},"institutions":[{"id":"https://openalex.org/I90610280","display_name":"South China University of Technology","ror":"https://ror.org/0530pts50","country_code":"CN","type":"education","lineage":["https://openalex.org/I90610280"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Ting Tao","raw_affiliation_strings":["School of Mathematics, South China University of Technology, Guangzhou, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Mathematics, South China University of Technology, Guangzhou, China","institution_ids":["https://openalex.org/I90610280"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5102446496","display_name":"Yitian Qian","orcid":null},"institutions":[{"id":"https://openalex.org/I90610280","display_name":"South China University of Technology","ror":"https://ror.org/0530pts50","country_code":"CN","type":"education","lineage":["https://openalex.org/I90610280"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yitian Qian","raw_affiliation_strings":["School of Mathematics, South China University of Technology, Guangzhou, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Mathematics, South China University of Technology, Guangzhou, China","institution_ids":["https://openalex.org/I90610280"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5090153413","display_name":"Shaohua Pan","orcid":"https://orcid.org/0000-0002-6261-5268"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Shaohua Pan","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":1.2698,"has_fulltext":false,"cited_by_count":11,"citation_normalized_percentile":{"value":0.73277808,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":94,"max":99},"biblio":{"volume":"32","issue":"2","first_page":"959","last_page":"988"},"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/T10638","display_name":"Optical measurement and interference techniques","score":0.9829000234603882,"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/T10801","display_name":"Synthetic Aperture Radar (SAR) Applications and Techniques","score":0.982699990272522,"subfield":{"id":"https://openalex.org/subfields/2202","display_name":"Aerospace Engineering"},"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/mathematics","display_name":"Mathematics","score":0.8394362330436707},{"id":"https://openalex.org/keywords/matrix-completion","display_name":"Matrix completion","score":0.7044572234153748},{"id":"https://openalex.org/keywords/extrapolation","display_name":"Extrapolation","score":0.6398624181747437},{"id":"https://openalex.org/keywords/low-rank-approximation","display_name":"Low-rank approximation","score":0.5997381210327148},{"id":"https://openalex.org/keywords/norm","display_name":"Norm (philosophy)","score":0.5944266319274902},{"id":"https://openalex.org/keywords/matrix-norm","display_name":"Matrix norm","score":0.5911546945571899},{"id":"https://openalex.org/keywords/factorization","display_name":"Factorization","score":0.5911270380020142},{"id":"https://openalex.org/keywords/computation","display_name":"Computation","score":0.5241734981536865},{"id":"https://openalex.org/keywords/rank","display_name":"Rank (graph theory)","score":0.4949328303337097},{"id":"https://openalex.org/keywords/matrix","display_name":"Matrix (chemical analysis)","score":0.4724355638027191},{"id":"https://openalex.org/keywords/applied-mathematics","display_name":"Applied mathematics","score":0.4686996638774872},{"id":"https://openalex.org/keywords/regular-polygon","display_name":"Regular polygon","score":0.42064374685287476},{"id":"https://openalex.org/keywords/combinatorics","display_name":"Combinatorics","score":0.39567244052886963},{"id":"https://openalex.org/keywords/mathematical-optimization","display_name":"Mathematical optimization","score":0.3700779676437378},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.29440751671791077},{"id":"https://openalex.org/keywords/mathematical-analysis","display_name":"Mathematical analysis","score":0.16593125462532043},{"id":"https://openalex.org/keywords/geometry","display_name":"Geometry","score":0.0653543472290039}],"concepts":[{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.8394362330436707},{"id":"https://openalex.org/C2778459887","wikidata":"https://www.wikidata.org/wiki/Q6787865","display_name":"Matrix completion","level":3,"score":0.7044572234153748},{"id":"https://openalex.org/C132459708","wikidata":"https://www.wikidata.org/wiki/Q744069","display_name":"Extrapolation","level":2,"score":0.6398624181747437},{"id":"https://openalex.org/C90199385","wikidata":"https://www.wikidata.org/wiki/Q6692777","display_name":"Low-rank approximation","level":3,"score":0.5997381210327148},{"id":"https://openalex.org/C191795146","wikidata":"https://www.wikidata.org/wiki/Q3878446","display_name":"Norm (philosophy)","level":2,"score":0.5944266319274902},{"id":"https://openalex.org/C92207270","wikidata":"https://www.wikidata.org/wiki/Q939253","display_name":"Matrix norm","level":3,"score":0.5911546945571899},{"id":"https://openalex.org/C187834632","wikidata":"https://www.wikidata.org/wiki/Q188804","display_name":"Factorization","level":2,"score":0.5911270380020142},{"id":"https://openalex.org/C45374587","wikidata":"https://www.wikidata.org/wiki/Q12525525","display_name":"Computation","level":2,"score":0.5241734981536865},{"id":"https://openalex.org/C164226766","wikidata":"https://www.wikidata.org/wiki/Q7293202","display_name":"Rank (graph theory)","level":2,"score":0.4949328303337097},{"id":"https://openalex.org/C106487976","wikidata":"https://www.wikidata.org/wiki/Q685816","display_name":"Matrix (chemical analysis)","level":2,"score":0.4724355638027191},{"id":"https://openalex.org/C28826006","wikidata":"https://www.wikidata.org/wiki/Q33521","display_name":"Applied mathematics","level":1,"score":0.4686996638774872},{"id":"https://openalex.org/C112680207","wikidata":"https://www.wikidata.org/wiki/Q714886","display_name":"Regular polygon","level":2,"score":0.42064374685287476},{"id":"https://openalex.org/C114614502","wikidata":"https://www.wikidata.org/wiki/Q76592","display_name":"Combinatorics","level":1,"score":0.39567244052886963},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.3700779676437378},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.29440751671791077},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.16593125462532043},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0653543472290039},{"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/C17744445","wikidata":"https://www.wikidata.org/wiki/Q36442","display_name":"Political science","level":0,"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/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C199539241","wikidata":"https://www.wikidata.org/wiki/Q7748","display_name":"Law","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},{"id":"https://openalex.org/C163716315","wikidata":"https://www.wikidata.org/wiki/Q901177","display_name":"Gaussian","level":2,"score":0.0},{"id":"https://openalex.org/C25023664","wikidata":"https://www.wikidata.org/wiki/Q1575637","display_name":"Hankel matrix","level":2,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1137/20m136205x","is_oa":false,"landing_page_url":"https://doi.org/10.1137/20m136205x","pdf_url":null,"source":{"id":"https://openalex.org/S928796702","display_name":"SIAM Journal on Optimization","issn_l":"1052-6234","issn":["1052-6234","1095-7189"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320508","host_organization_name":"Society for Industrial and Applied Mathematics","host_organization_lineage":["https://openalex.org/P4310320508"],"host_organization_lineage_names":["Society for Industrial and Applied Mathematics"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"SIAM Journal on Optimization","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G3132854653","display_name":"\u4f4e\u79e9\u77e9\u9635\u4f18\u5316\u95ee\u9898\u7684\u7a33\u5b9a\u6027\u7814\u7a76\u53ca\u7b97\u6cd5\u4e2d\u7684\u5e94\u7528","funder_award_id":"11971177","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G3216467020","display_name":null,"funder_award_id":"2020A1515010408","funder_id":"https://openalex.org/F4320337111","funder_display_name":"Basic and Applied Basic Research Foundation of Guangdong Province"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320337111","display_name":"Basic and Applied Basic Research Foundation of Guangdong Province","ror":null}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":42,"referenced_works":["https://openalex.org/W1529624360","https://openalex.org/W1863732927","https://openalex.org/W2011359124","https://openalex.org/W2027982384","https://openalex.org/W2045377163","https://openalex.org/W2059958128","https://openalex.org/W2060204507","https://openalex.org/W2106005123","https://openalex.org/W2111297856","https://openalex.org/W2118550318","https://openalex.org/W2122090912","https://openalex.org/W2129732816","https://openalex.org/W2136690855","https://openalex.org/W2143075842","https://openalex.org/W2162451874","https://openalex.org/W2268674159","https://openalex.org/W2339666411","https://openalex.org/W2528650782","https://openalex.org/W2549127690","https://openalex.org/W2566608758","https://openalex.org/W2586353914","https://openalex.org/W2592246480","https://openalex.org/W2604130501","https://openalex.org/W2611328865","https://openalex.org/W2789612570","https://openalex.org/W2915116423","https://openalex.org/W2931810883","https://openalex.org/W2949419207","https://openalex.org/W2963014255","https://openalex.org/W2963292690","https://openalex.org/W2963375486","https://openalex.org/W2963404710","https://openalex.org/W2963449128","https://openalex.org/W2963579802","https://openalex.org/W2963648037","https://openalex.org/W2963799907","https://openalex.org/W2963965252","https://openalex.org/W2964146881","https://openalex.org/W2964316995","https://openalex.org/W3105489725","https://openalex.org/W3105952791","https://openalex.org/W3198205161"],"related_works":["https://openalex.org/W2964006653","https://openalex.org/W2788826952","https://openalex.org/W4302315572","https://openalex.org/W2084983808","https://openalex.org/W2325477568","https://openalex.org/W1991825408","https://openalex.org/W4318564253","https://openalex.org/W1969698720","https://openalex.org/W1507830821","https://openalex.org/W2963965423"],"abstract_inverted_index":{"This":[0],"paper":[1],"is":[2,24,61,78],"concerned":[3],"with":[4,48,69,76,106,114,123],"the":[5,74,89,94,102,124,130,137],"column":[6,19,28,138],"$\\ell_{2,0}$-regularized":[7,139],"factorization":[8,127,140],"model":[9,128,134,141],"of":[10,21,30,148],"low-rank":[11,33],"matrix":[12,103],"recovery":[13],"problems":[14],"and":[15,32,50,73,98,116,120,129,151],"its":[16],"computation.":[17],"The":[18],"$\\ell_{2,0}$-norm":[20],"factor":[22,67],"matrices":[23],"introduced":[25],"to":[26,63,81,101],"promote":[27],"sparsity":[29],"factors":[31],"solutions.":[34],"For":[35],"this":[36],"nonconvex":[37,85],"discontinuous":[38],"optimization":[39],"problem,":[40],"we":[41],"develop":[42],"an":[43,65,143],"alternating":[44,58],"majorization-minimization":[45],"(AMM)":[46],"method":[47,60],"extrapolation":[49,77],"a":[51,56,83],"hybrid":[52],"AMM":[53,75,96],"in":[54,145],"which":[55],"majorized":[57],"proximal":[59],"proposed":[62,95],"seek":[64],"initial":[66],"pair":[68],"less":[70,154],"nonzero":[71],"columns":[72],"then":[79],"employed":[80],"minimize":[82],"smooth":[84],"loss.":[86],"We":[87],"provide":[88],"global":[90],"convergence":[91],"analysis":[92],"for":[93],"methods":[97],"apply":[99],"them":[100],"completion":[104],"problem":[105],"nonuniform":[107],"sampling":[108],"schemes.":[109],"Numerical":[110],"experiments":[111],"are":[112],"conducted":[113],"synthetic":[115],"real":[117],"data":[118],"examples,":[119],"comparison":[121],"results":[122],"nuclear-norm":[125],"regularized":[126,132],"max-norm":[131],"convex":[133],"show":[135],"that":[136],"has":[142],"advantage":[144],"offering":[146],"solutions":[147],"lower":[149],"error":[150],"rank":[152],"within":[153],"time.":[155]},"counts_by_year":[{"year":2026,"cited_by_count":3},{"year":2025,"cited_by_count":6},{"year":2024,"cited_by_count":2}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
