{"id":"https://openalex.org/W2112680395","doi":"https://doi.org/10.1109/isit.2010.5513563","title":"Regularization for matrix completion","display_name":"Regularization for matrix completion","publication_year":2010,"publication_date":"2010-06-01","ids":{"openalex":"https://openalex.org/W2112680395","doi":"https://doi.org/10.1109/isit.2010.5513563","mag":"2112680395"},"language":"en","primary_location":{"id":"doi:10.1109/isit.2010.5513563","is_oa":false,"landing_page_url":"https://doi.org/10.1109/isit.2010.5513563","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2010 IEEE International Symposium on Information Theory","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/A5007082744","display_name":"Raghunandan H. Keshavan","orcid":null},"institutions":[{"id":"https://openalex.org/I97018004","display_name":"Stanford University","ror":"https://ror.org/00f54p054","country_code":"US","type":"education","lineage":["https://openalex.org/I97018004"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Raghunandan H. Keshavan","raw_affiliation_strings":["Department of Electrical Engineering, University of Stanford, USA","Departments of Electrical Engineering, Stanford University, USA"],"affiliations":[{"raw_affiliation_string":"Department of Electrical Engineering, University of Stanford, USA","institution_ids":["https://openalex.org/I97018004"]},{"raw_affiliation_string":"Departments of Electrical Engineering, Stanford University, USA","institution_ids":["https://openalex.org/I97018004"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5011999109","display_name":"Andrea Montanari","orcid":"https://orcid.org/0000-0002-0267-8574"},"institutions":[{"id":"https://openalex.org/I97018004","display_name":"Stanford University","ror":"https://ror.org/00f54p054","country_code":"US","type":"education","lineage":["https://openalex.org/I97018004"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Andrea Montanari","raw_affiliation_strings":["Stanford University, Stanford, CA, US","Departments of Electrical Engineering, Stanford University, USA"],"affiliations":[{"raw_affiliation_string":"Stanford University, Stanford, CA, US","institution_ids":["https://openalex.org/I97018004"]},{"raw_affiliation_string":"Departments of Electrical Engineering, Stanford University, USA","institution_ids":["https://openalex.org/I97018004"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5007082744"],"corresponding_institution_ids":["https://openalex.org/I97018004"],"apc_list":null,"apc_paid":null,"fwci":2.3716,"has_fulltext":false,"cited_by_count":16,"citation_normalized_percentile":{"value":0.89032552,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":96},"biblio":{"volume":null,"issue":null,"first_page":null,"last_page":null},"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/T11739","display_name":"Microwave Imaging and Scattering Analysis","score":0.9939000010490417,"subfield":{"id":"https://openalex.org/subfields/2204","display_name":"Biomedical Engineering"},"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":0.9927999973297119,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/matrix-completion","display_name":"Matrix completion","score":0.6787217855453491},{"id":"https://openalex.org/keywords/overfitting","display_name":"Overfitting","score":0.6695005297660828},{"id":"https://openalex.org/keywords/low-rank-approximation","display_name":"Low-rank approximation","score":0.6138522624969482},{"id":"https://openalex.org/keywords/regularization","display_name":"Regularization (linguistics)","score":0.6022480130195618},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5908315181732178},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.5522385835647583},{"id":"https://openalex.org/keywords/noise","display_name":"Noise (video)","score":0.48651832342147827},{"id":"https://openalex.org/keywords/matrix","display_name":"Matrix (chemical analysis)","score":0.4482026696205139},{"id":"https://openalex.org/keywords/stochastic-gradient-descent","display_name":"Stochastic gradient descent","score":0.430698424577713},{"id":"https://openalex.org/keywords/mathematical-optimization","display_name":"Mathematical optimization","score":0.38141554594039917},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.3700679838657379},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.3217059373855591},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.1486813724040985}],"concepts":[{"id":"https://openalex.org/C2778459887","wikidata":"https://www.wikidata.org/wiki/Q6787865","display_name":"Matrix completion","level":3,"score":0.6787217855453491},{"id":"https://openalex.org/C22019652","wikidata":"https://www.wikidata.org/wiki/Q331309","display_name":"Overfitting","level":3,"score":0.6695005297660828},{"id":"https://openalex.org/C90199385","wikidata":"https://www.wikidata.org/wiki/Q6692777","display_name":"Low-rank approximation","level":3,"score":0.6138522624969482},{"id":"https://openalex.org/C2776135515","wikidata":"https://www.wikidata.org/wiki/Q17143721","display_name":"Regularization (linguistics)","level":2,"score":0.6022480130195618},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5908315181732178},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.5522385835647583},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.48651832342147827},{"id":"https://openalex.org/C106487976","wikidata":"https://www.wikidata.org/wiki/Q685816","display_name":"Matrix (chemical analysis)","level":2,"score":0.4482026696205139},{"id":"https://openalex.org/C206688291","wikidata":"https://www.wikidata.org/wiki/Q7617819","display_name":"Stochastic gradient descent","level":3,"score":0.430698424577713},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.38141554594039917},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3700679838657379},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.3217059373855591},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.1486813724040985},{"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/C25023664","wikidata":"https://www.wikidata.org/wiki/Q1575637","display_name":"Hankel matrix","level":2,"score":0.0},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","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/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/C159985019","wikidata":"https://www.wikidata.org/wiki/Q181790","display_name":"Composite material","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/isit.2010.5513563","is_oa":false,"landing_page_url":"https://doi.org/10.1109/isit.2010.5513563","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2010 IEEE International Symposium on Information Theory","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"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":20,"referenced_works":["https://openalex.org/W1976618413","https://openalex.org/W2000157792","https://openalex.org/W2039953809","https://openalex.org/W2047071281","https://openalex.org/W2095004008","https://openalex.org/W2097702467","https://openalex.org/W2097714737","https://openalex.org/W2112680395","https://openalex.org/W2122090912","https://openalex.org/W2124608575","https://openalex.org/W2146130798","https://openalex.org/W2611328865","https://openalex.org/W2616032753","https://openalex.org/W2949834189","https://openalex.org/W2952716509","https://openalex.org/W3003365835","https://openalex.org/W3098569320","https://openalex.org/W3104309687","https://openalex.org/W6677671969","https://openalex.org/W6682042988"],"related_works":["https://openalex.org/W2952489973","https://openalex.org/W2106005123","https://openalex.org/W4300776969","https://openalex.org/W2266965707","https://openalex.org/W2108753466","https://openalex.org/W2084983808","https://openalex.org/W2906317811","https://openalex.org/W4318564253","https://openalex.org/W2994409951","https://openalex.org/W2402491700"],"abstract_inverted_index":{"We":[0],"consider":[1],"the":[2,41,48,54,61,96,103,112,117],"problem":[3],"of":[4,13,16,119],"reconstructing":[5],"a":[6,14,79,90,107],"low":[7],"rank":[8],"matrix":[9],"from":[10],"noisy":[11],"observations":[12],"subset":[15],"its":[17],"entries.":[18,121],"This":[19],"task":[20],"has":[21],"applications":[22],"in":[23,95],"statistical":[24],"learning,":[25],"computer":[26],"vision,":[27],"and":[28,64,94,115],"signal":[29,63],"processing.":[30],"In":[31,51,71],"these":[32],"contexts,":[33],"`noise'":[34],"generically":[35],"refers":[36],"to":[37,40,60,68,73],"any":[38],"contribution":[39],"data":[42],"that":[43,102,138],"is":[44,57,66,141],"not":[45],"captured":[46],"by":[47],"low-rank":[49],"model.":[50],"most":[52],"applications,":[53],"noise":[55,92,113],"level":[56,114],"large":[58,97],"compared":[59],"underlying":[62],"it":[65],"important":[67],"avoid":[69],"overfitting.":[70],"order":[72],"tackle":[74],"this":[75,139],"problem,":[76],"we":[77,100],"define":[78],"regularized":[80],"cost":[81,123],"function":[82,124],"well":[83],"suited":[84],"for":[85],"spectral":[86],"reconstruction":[87],"methods.":[88],"Within":[89],"random":[91],"model,":[93],"system":[98],"limit,":[99],"prove":[101],"resulting":[104],"accuracy":[105],"undergoes":[106],"phase":[108],"transition":[109],"depending":[110],"on":[111,116],"fraction":[118],"observed":[120],"The":[122],"can":[125],"be":[126],"minimized":[127],"using":[128],"OPTSPACE":[129],"(a":[130],"manifold":[131],"gradient":[132],"descent":[133],"algorithm).":[134],"Numerical":[135],"simulations":[136],"show":[137],"approach":[140],"competitive":[142],"with":[143],"state-of-the-art":[144],"alternatives.":[145]},"counts_by_year":[{"year":2021,"cited_by_count":1},{"year":2020,"cited_by_count":1},{"year":2019,"cited_by_count":1},{"year":2017,"cited_by_count":1},{"year":2016,"cited_by_count":2},{"year":2015,"cited_by_count":1},{"year":2014,"cited_by_count":2},{"year":2013,"cited_by_count":2}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
