{"id":"https://openalex.org/W2023722580","doi":"https://doi.org/10.1137/090756855","title":"NESTA: A Fast and Accurate First-Order Method for Sparse Recovery","display_name":"NESTA: A Fast and Accurate First-Order Method for Sparse Recovery","publication_year":2011,"publication_date":"2011-01-01","ids":{"openalex":"https://openalex.org/W2023722580","doi":"https://doi.org/10.1137/090756855","mag":"2023722580"},"language":"en","primary_location":{"id":"doi:10.1137/090756855","is_oa":false,"landing_page_url":"https://doi.org/10.1137/090756855","pdf_url":null,"source":{"id":"https://openalex.org/S152600803","display_name":"SIAM Journal on Imaging Sciences","issn_l":"1936-4954","issn":["1936-4954"],"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 Imaging Sciences","raw_type":"journal-article"},"type":"article","indexed_in":["arxiv","crossref"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/0904.3367","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":null,"display_name":"Stephen Becker","orcid":null},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Stephen Becker","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":null,"display_name":"J\u00e9r\u00f4me Bobin","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"J\u00e9r\u00f4me Bobin","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"last","author":{"id":null,"display_name":"Emmanuel J. Cand\u00e8s","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Emmanuel J. Cand\u00e8s","raw_affiliation_strings":[],"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":69.3651,"has_fulltext":false,"cited_by_count":823,"citation_normalized_percentile":{"value":0.99970368,"is_in_top_1_percent":true,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":99,"max":100},"biblio":{"volume":"4","issue":"1","first_page":"1","last_page":"39"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10500","display_name":"Sparse and Compressive Sensing Techniques","score":0.9682999849319458,"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":0.9682999849319458,"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/T10522","display_name":"Medical Imaging Techniques and Applications","score":0.007699999958276749,"subfield":{"id":"https://openalex.org/subfields/2741","display_name":"Radiology, Nuclear Medicine and Imaging"},"field":{"id":"https://openalex.org/fields/27","display_name":"Medicine"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}},{"id":"https://openalex.org/T11105","display_name":"Advanced Image Processing Techniques","score":0.004800000227987766,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/compressed-sensing","display_name":"Compressed sensing","score":0.7645999789237976},{"id":"https://openalex.org/keywords/smoothing","display_name":"Smoothing","score":0.7116000056266785},{"id":"https://openalex.org/keywords/range","display_name":"Range (aeronautics)","score":0.595300018787384},{"id":"https://openalex.org/keywords/minification","display_name":"Minification","score":0.5364999771118164},{"id":"https://openalex.org/keywords/convex-optimization","display_name":"Convex optimization","score":0.49390000104904175},{"id":"https://openalex.org/keywords/code","display_name":"Code (set theory)","score":0.4927999973297119},{"id":"https://openalex.org/keywords/signal-reconstruction","display_name":"Signal reconstruction","score":0.48429998755455017},{"id":"https://openalex.org/keywords/iterative-reconstruction","display_name":"Iterative reconstruction","score":0.427700012922287},{"id":"https://openalex.org/keywords/field","display_name":"Field (mathematics)","score":0.40700000524520874}],"concepts":[{"id":"https://openalex.org/C124851039","wikidata":"https://www.wikidata.org/wiki/Q2665459","display_name":"Compressed sensing","level":2,"score":0.7645999789237976},{"id":"https://openalex.org/C3770464","wikidata":"https://www.wikidata.org/wiki/Q775963","display_name":"Smoothing","level":2,"score":0.7116000056266785},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6937000155448914},{"id":"https://openalex.org/C204323151","wikidata":"https://www.wikidata.org/wiki/Q905424","display_name":"Range (aeronautics)","level":2,"score":0.595300018787384},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.5723999738693237},{"id":"https://openalex.org/C147764199","wikidata":"https://www.wikidata.org/wiki/Q6865248","display_name":"Minification","level":2,"score":0.5364999771118164},{"id":"https://openalex.org/C157972887","wikidata":"https://www.wikidata.org/wiki/Q463359","display_name":"Convex optimization","level":3,"score":0.49390000104904175},{"id":"https://openalex.org/C2776760102","wikidata":"https://www.wikidata.org/wiki/Q5139990","display_name":"Code (set theory)","level":3,"score":0.4927999973297119},{"id":"https://openalex.org/C70958404","wikidata":"https://www.wikidata.org/wiki/Q7512728","display_name":"Signal reconstruction","level":4,"score":0.48429998755455017},{"id":"https://openalex.org/C141379421","wikidata":"https://www.wikidata.org/wiki/Q6094427","display_name":"Iterative reconstruction","level":2,"score":0.427700012922287},{"id":"https://openalex.org/C9652623","wikidata":"https://www.wikidata.org/wiki/Q190109","display_name":"Field (mathematics)","level":2,"score":0.40700000524520874},{"id":"https://openalex.org/C191795146","wikidata":"https://www.wikidata.org/wiki/Q3878446","display_name":"Norm (philosophy)","level":2,"score":0.3977000117301941},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.3871999979019165},{"id":"https://openalex.org/C2780365114","wikidata":"https://www.wikidata.org/wiki/Q169478","display_name":"MATLAB","level":2,"score":0.37070000171661377},{"id":"https://openalex.org/C112680207","wikidata":"https://www.wikidata.org/wiki/Q714886","display_name":"Regular polygon","level":2,"score":0.36559998989105225},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.33390000462532043},{"id":"https://openalex.org/C104267543","wikidata":"https://www.wikidata.org/wiki/Q208163","display_name":"Signal processing","level":3,"score":0.33079999685287476},{"id":"https://openalex.org/C137836250","wikidata":"https://www.wikidata.org/wiki/Q984063","display_name":"Optimization problem","level":2,"score":0.3278999924659729},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.3231000006198883},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.3151000142097473},{"id":"https://openalex.org/C43126263","wikidata":"https://www.wikidata.org/wiki/Q128751","display_name":"Source code","level":2,"score":0.2935999929904938},{"id":"https://openalex.org/C2779843651","wikidata":"https://www.wikidata.org/wiki/Q7390335","display_name":"SIGNAL (programming language)","level":2,"score":0.2867000102996826},{"id":"https://openalex.org/C2781170535","wikidata":"https://www.wikidata.org/wiki/Q30587856","display_name":"Noisy data","level":2,"score":0.28600001335144043},{"id":"https://openalex.org/C56372850","wikidata":"https://www.wikidata.org/wiki/Q1050404","display_name":"Sparse matrix","level":3,"score":0.2802000045776367},{"id":"https://openalex.org/C106430172","wikidata":"https://www.wikidata.org/wiki/Q6002272","display_name":"Image restoration","level":4,"score":0.2797999978065491},{"id":"https://openalex.org/C124066611","wikidata":"https://www.wikidata.org/wiki/Q28684319","display_name":"Sparse approximation","level":2,"score":0.27399998903274536},{"id":"https://openalex.org/C9417928","wikidata":"https://www.wikidata.org/wiki/Q1070689","display_name":"Image processing","level":3,"score":0.2655999958515167},{"id":"https://openalex.org/C6802819","wikidata":"https://www.wikidata.org/wiki/Q1072174","display_name":"Linear system","level":2,"score":0.26159998774528503},{"id":"https://openalex.org/C2779898584","wikidata":"https://www.wikidata.org/wiki/Q7820109","display_name":"Reconstruction algorithm","level":3,"score":0.250900000333786}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.1137/090756855","is_oa":false,"landing_page_url":"https://doi.org/10.1137/090756855","pdf_url":null,"source":{"id":"https://openalex.org/S152600803","display_name":"SIAM Journal on Imaging Sciences","issn_l":"1936-4954","issn":["1936-4954"],"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 Imaging Sciences","raw_type":"journal-article"},{"id":"pmh:oai:arXiv.org:0904.3367","is_oa":true,"landing_page_url":"http://arxiv.org/abs/0904.3367","pdf_url":"https://arxiv.org/pdf/0904.3367","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":null,"raw_type":"text"},{"id":"pmh:oai:authors.library.caltech.edu:23706","is_oa":false,"landing_page_url":"https://resolver.caltech.edu/CaltechAUTHORS:20110518-092411645","pdf_url":null,"source":{"id":"https://openalex.org/S4306402161","display_name":"CaltechAUTHORS (California Institute of Technology)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I122411786","host_organization_name":"California Institute of Technology","host_organization_lineage":["https://openalex.org/I122411786"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"Article"}],"best_oa_location":{"id":"pmh:oai:arXiv.org:0904.3367","is_oa":true,"landing_page_url":"http://arxiv.org/abs/0904.3367","pdf_url":"https://arxiv.org/pdf/0904.3367","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":null,"raw_type":"text"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":47,"referenced_works":["https://openalex.org/W1973734200","https://openalex.org/W1977905043","https://openalex.org/W1984553293","https://openalex.org/W1986931325","https://openalex.org/W1996287810","https://openalex.org/W2006262045","https://openalex.org/W2009702064","https://openalex.org/W2022611944","https://openalex.org/W2028349405","https://openalex.org/W2028452438","https://openalex.org/W2030620341","https://openalex.org/W2034260606","https://openalex.org/W2048511268","https://openalex.org/W2049602132","https://openalex.org/W2061315188","https://openalex.org/W2062102668","https://openalex.org/W2076605490","https://openalex.org/W2082473969","https://openalex.org/W2083042020","https://openalex.org/W2098012923","https://openalex.org/W2098602977","https://openalex.org/W2100556411","https://openalex.org/W2100705753","https://openalex.org/W2101675075","https://openalex.org/W2107844156","https://openalex.org/W2107861471","https://openalex.org/W2109449402","https://openalex.org/W2110505738","https://openalex.org/W2113740359","https://openalex.org/W2115447612","https://openalex.org/W2115528090","https://openalex.org/W2115706991","https://openalex.org/W2122890444","https://openalex.org/W2126607811","https://openalex.org/W2129638195","https://openalex.org/W2135046866","https://openalex.org/W2138616240","https://openalex.org/W2142058898","https://openalex.org/W2142308565","https://openalex.org/W2145096794","https://openalex.org/W2145534432","https://openalex.org/W2163973643","https://openalex.org/W2167732364","https://openalex.org/W2289917018","https://openalex.org/W3022380717","https://openalex.org/W4250955649","https://openalex.org/W4294541781"],"related_works":[],"abstract_inverted_index":{"Accurate":[0],"signal":[1],"recovery":[2],"or":[3],"image":[4],"reconstruction":[5,68,97],"from":[6,45],"indirect":[7],"and":[8,39,55,80,91,99,168],"possibly":[9],"undersampled":[10],"data":[11],"is":[12,29,60,73,78,89,102,184,189],"a":[13,36,112,134,193],"topic":[14],"of":[15,26,96,115,124,177],"considerable":[16],"interest;":[17],"for":[18,63,158],"example,":[19],"the":[20,23,105,121,152,174,197],"literature":[21],"in":[22,104,181,196],"recent":[24],"field":[25],"compressed":[27,66],"sensing":[28,67],"already":[30],"quite":[31],"immense.":[32],"This":[33],"paper":[34],"applies":[35],"smoothing":[37],"technique":[38],"an":[40],"accelerated":[41],"first-order":[42],"algorithm,":[43],"both":[44],"Nesterov":[46],"[Math.":[47],"Program.":[48],"Ser.":[49],"A,":[50],"103":[51],"(2005),":[52],"pp.":[53],"127\u2013152],":[54],"demonstrates":[56],"that":[57,107,139],"this":[58,140],"approach":[59],"ideally":[61],"suited":[62],"solving":[64],"large-scale":[65],"problems":[69,116,157],"as":[70,165,192],"(1)":[71],"it":[72,77,88,101],"computationally":[74],"efficient,":[75],"(2)":[76],"accurate":[79],"returns":[81],"solutions":[82],"with":[83,144],"several":[84,125],"correct":[85],"digits,":[86],"(3)":[87],"flexible":[90],"amenable":[92],"to":[93,154,172],"many":[94],"kinds":[95],"problems,":[98],"(4)":[100],"robust":[103],"sense":[106],"its":[108],"excellent":[109],"performance":[110],"across":[111],"wide":[113],"range":[114,137],"does":[117],"not":[118,185],"depend":[119],"on":[120,130],"fine":[122],"tuning":[123],"parameters.":[126],"Comprehensive":[127],"numerical":[128],"experiments":[129],"realistic":[131],"signals":[132],"exhibiting":[133],"large":[135],"dynamic":[136],"show":[138],"algorithm":[141,153],"compares":[142],"favorably":[143],"recently":[145],"proposed":[146],"state-of-the-art":[147],"methods.":[148],"We":[149],"also":[150],"apply":[151],"solve":[155],"other":[156],"which":[159,182],"there":[160],"are":[161],"fewer":[162],"alternatives,":[163],"such":[164],"total-variation":[166],"minimization":[167],"convex":[169],"programs":[170],"seeking":[171],"minimize":[173],"$\\ell_1$":[175],"norm":[176],"$Wx$":[178],"under":[179],"constraints,":[180],"W":[183],"diagonal.":[186],"The":[187],"code":[188],"available":[190],"online":[191],"free":[194],"package":[195],"MATLAB":[198],"language.":[199]},"counts_by_year":[{"year":2026,"cited_by_count":5},{"year":2025,"cited_by_count":17},{"year":2024,"cited_by_count":26},{"year":2023,"cited_by_count":23},{"year":2022,"cited_by_count":32},{"year":2021,"cited_by_count":84},{"year":2020,"cited_by_count":47},{"year":2019,"cited_by_count":62},{"year":2018,"cited_by_count":80},{"year":2017,"cited_by_count":84},{"year":2016,"cited_by_count":88},{"year":2015,"cited_by_count":72},{"year":2014,"cited_by_count":70},{"year":2013,"cited_by_count":53},{"year":2012,"cited_by_count":45}],"updated_date":"2026-04-05T17:49:38.594831","created_date":"2016-06-24T00:00:00"}