{"id":"https://openalex.org/W2963597653","doi":"https://doi.org/10.1109/tit.2019.2921757","title":"Sub-Linear Time Support Recovery for Compressed Sensing Using Sparse-Graph Codes","display_name":"Sub-Linear Time Support Recovery for Compressed Sensing Using Sparse-Graph Codes","publication_year":2019,"publication_date":"2019-06-11","ids":{"openalex":"https://openalex.org/W2963597653","doi":"https://doi.org/10.1109/tit.2019.2921757","mag":"2963597653"},"language":"en","primary_location":{"id":"doi:10.1109/tit.2019.2921757","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tit.2019.2921757","pdf_url":null,"source":{"id":"https://openalex.org/S4502562","display_name":"IEEE Transactions on Information Theory","issn_l":"0018-9448","issn":["0018-9448","1557-9654"],"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 Transactions on Information Theory","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/A5100785848","display_name":"Li Xiao","orcid":"https://orcid.org/0000-0001-8513-6334"},"institutions":[{"id":"https://openalex.org/I95457486","display_name":"University of California, Berkeley","ror":"https://ror.org/01an7q238","country_code":"US","type":"education","lineage":["https://openalex.org/I95457486"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Xiao Li","raw_affiliation_strings":["Department of EECS, UC Berkeley, Berkeley, CA, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of EECS, UC Berkeley, Berkeley, CA, USA","institution_ids":["https://openalex.org/I95457486"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5001139821","display_name":"Dong Yin","orcid":"https://orcid.org/0000-0002-2358-0816"},"institutions":[{"id":"https://openalex.org/I95457486","display_name":"University of California, Berkeley","ror":"https://ror.org/01an7q238","country_code":"US","type":"education","lineage":["https://openalex.org/I95457486"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Dong Yin","raw_affiliation_strings":["Department of EECS, UC Berkeley, Berkeley, CA, USA"],"raw_orcid":"https://orcid.org/0000-0002-2358-0816","affiliations":[{"raw_affiliation_string":"Department of EECS, UC Berkeley, Berkeley, CA, USA","institution_ids":["https://openalex.org/I95457486"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5030647153","display_name":"Sameer Pawar","orcid":"https://orcid.org/0000-0001-8954-7747"},"institutions":[{"id":"https://openalex.org/I95457486","display_name":"University of California, Berkeley","ror":"https://ror.org/01an7q238","country_code":"US","type":"education","lineage":["https://openalex.org/I95457486"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Sameer Pawar","raw_affiliation_strings":["Department of EECS, UC Berkeley, Berkeley, CA, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of EECS, UC Berkeley, Berkeley, CA, USA","institution_ids":["https://openalex.org/I95457486"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5040270189","display_name":"Ramtin Pedarsani","orcid":"https://orcid.org/0000-0002-1126-0292"},"institutions":[{"id":"https://openalex.org/I154570441","display_name":"University of California, Santa Barbara","ror":"https://ror.org/02t274463","country_code":"US","type":"education","lineage":["https://openalex.org/I154570441"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Ramtin Pedarsani","raw_affiliation_strings":["Department of ECE, UC Santa Barbara, Santa Barbara, CA, USA"],"raw_orcid":"https://orcid.org/0000-0002-1126-0292","affiliations":[{"raw_affiliation_string":"Department of ECE, UC Santa Barbara, Santa Barbara, CA, USA","institution_ids":["https://openalex.org/I154570441"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5030620564","display_name":"Kannan Ramchandran","orcid":"https://orcid.org/0000-0002-4567-328X"},"institutions":[{"id":"https://openalex.org/I95457486","display_name":"University of California, Berkeley","ror":"https://ror.org/01an7q238","country_code":"US","type":"education","lineage":["https://openalex.org/I95457486"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Kannan Ramchandran","raw_affiliation_strings":["Department of EECS, UC Berkeley, Berkeley, CA, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of EECS, UC Berkeley, Berkeley, CA, USA","institution_ids":["https://openalex.org/I95457486"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":2.0722,"has_fulltext":false,"cited_by_count":17,"citation_normalized_percentile":{"value":0.8508023,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":97},"biblio":{"volume":"65","issue":"10","first_page":"6580","last_page":"6619"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10500","display_name":"Sparse and Compressive Sensing Techniques","score":0.9998999834060669,"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":0.9998999834060669,"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/T10148","display_name":"Advanced MIMO Systems Optimization","score":0.9984999895095825,"subfield":{"id":"https://openalex.org/subfields/2208","display_name":"Electrical and Electronic 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/T11321","display_name":"Error Correcting Code Techniques","score":0.998199999332428,"subfield":{"id":"https://openalex.org/subfields/1705","display_name":"Computer Networks and Communications"},"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":0.8445127606391907},{"id":"https://openalex.org/keywords/decoding-methods","display_name":"Decoding methods","score":0.6641815304756165},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.5748898983001709},{"id":"https://openalex.org/keywords/dimension","display_name":"Dimension (graph theory)","score":0.5493360757827759},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5079007744789124},{"id":"https://openalex.org/keywords/sparse-matrix","display_name":"Sparse matrix","score":0.4997220039367676},{"id":"https://openalex.org/keywords/matrix","display_name":"Matrix (chemical analysis)","score":0.4884108901023865},{"id":"https://openalex.org/keywords/signal-reconstruction","display_name":"Signal reconstruction","score":0.4559089243412018},{"id":"https://openalex.org/keywords/basis-pursuit","display_name":"Basis pursuit","score":0.42928779125213623},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.3393864035606384},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.3364415764808655},{"id":"https://openalex.org/keywords/signal-processing","display_name":"Signal processing","score":0.32908865809440613},{"id":"https://openalex.org/keywords/combinatorics","display_name":"Combinatorics","score":0.20750421285629272},{"id":"https://openalex.org/keywords/matching-pursuit","display_name":"Matching pursuit","score":0.17331168055534363}],"concepts":[{"id":"https://openalex.org/C124851039","wikidata":"https://www.wikidata.org/wiki/Q2665459","display_name":"Compressed sensing","level":2,"score":0.8445127606391907},{"id":"https://openalex.org/C57273362","wikidata":"https://www.wikidata.org/wiki/Q576722","display_name":"Decoding methods","level":2,"score":0.6641815304756165},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.5748898983001709},{"id":"https://openalex.org/C33676613","wikidata":"https://www.wikidata.org/wiki/Q13415176","display_name":"Dimension (graph theory)","level":2,"score":0.5493360757827759},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5079007744789124},{"id":"https://openalex.org/C56372850","wikidata":"https://www.wikidata.org/wiki/Q1050404","display_name":"Sparse matrix","level":3,"score":0.4997220039367676},{"id":"https://openalex.org/C106487976","wikidata":"https://www.wikidata.org/wiki/Q685816","display_name":"Matrix (chemical analysis)","level":2,"score":0.4884108901023865},{"id":"https://openalex.org/C70958404","wikidata":"https://www.wikidata.org/wiki/Q7512728","display_name":"Signal reconstruction","level":4,"score":0.4559089243412018},{"id":"https://openalex.org/C99217422","wikidata":"https://www.wikidata.org/wiki/Q4867576","display_name":"Basis pursuit","level":4,"score":0.42928779125213623},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.3393864035606384},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.3364415764808655},{"id":"https://openalex.org/C104267543","wikidata":"https://www.wikidata.org/wiki/Q208163","display_name":"Signal processing","level":3,"score":0.32908865809440613},{"id":"https://openalex.org/C114614502","wikidata":"https://www.wikidata.org/wiki/Q76592","display_name":"Combinatorics","level":1,"score":0.20750421285629272},{"id":"https://openalex.org/C156872377","wikidata":"https://www.wikidata.org/wiki/Q6786281","display_name":"Matching pursuit","level":3,"score":0.17331168055534363},{"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/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","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/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},{"id":"https://openalex.org/C554190296","wikidata":"https://www.wikidata.org/wiki/Q47528","display_name":"Radar","level":2,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tit.2019.2921757","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tit.2019.2921757","pdf_url":null,"source":{"id":"https://openalex.org/S4502562","display_name":"IEEE Transactions on Information Theory","issn_l":"0018-9448","issn":["0018-9448","1557-9654"],"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 Transactions on Information Theory","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":87,"referenced_works":["https://openalex.org/W1493892051","https://openalex.org/W1536930200","https://openalex.org/W1591116419","https://openalex.org/W1620362451","https://openalex.org/W1635427980","https://openalex.org/W1672894909","https://openalex.org/W1674742109","https://openalex.org/W1806269746","https://openalex.org/W1971402995","https://openalex.org/W1974466705","https://openalex.org/W1985324531","https://openalex.org/W1991468147","https://openalex.org/W1993266883","https://openalex.org/W1994521750","https://openalex.org/W2006506233","https://openalex.org/W2009101269","https://openalex.org/W2014860393","https://openalex.org/W2030449718","https://openalex.org/W2033375925","https://openalex.org/W2034260606","https://openalex.org/W2035379331","https://openalex.org/W2046658845","https://openalex.org/W2047765680","https://openalex.org/W2050556604","https://openalex.org/W2068136251","https://openalex.org/W2082029531","https://openalex.org/W2096685801","https://openalex.org/W2098149254","https://openalex.org/W2099100030","https://openalex.org/W2100556411","https://openalex.org/W2101675075","https://openalex.org/W2103300200","https://openalex.org/W2104266187","https://openalex.org/W2104357403","https://openalex.org/W2106045225","https://openalex.org/W2107086875","https://openalex.org/W2109379066","https://openalex.org/W2111992537","https://openalex.org/W2115104320","https://openalex.org/W2115447612","https://openalex.org/W2127271355","https://openalex.org/W2127300249","https://openalex.org/W2127490352","https://openalex.org/W2128765501","https://openalex.org/W2129569662","https://openalex.org/W2130199634","https://openalex.org/W2135046866","https://openalex.org/W2135393523","https://openalex.org/W2137822056","https://openalex.org/W2138548210","https://openalex.org/W2140466267","https://openalex.org/W2140856955","https://openalex.org/W2141556672","https://openalex.org/W2142244720","https://openalex.org/W2143236825","https://openalex.org/W2145096794","https://openalex.org/W2147225015","https://openalex.org/W2149206122","https://openalex.org/W2150498905","https://openalex.org/W2157194148","https://openalex.org/W2169732368","https://openalex.org/W2173526877","https://openalex.org/W2289917018","https://openalex.org/W2296616510","https://openalex.org/W2407753648","https://openalex.org/W2499720122","https://openalex.org/W2532988047","https://openalex.org/W2571527823","https://openalex.org/W2588111195","https://openalex.org/W2607151738","https://openalex.org/W2885472922","https://openalex.org/W2963213854","https://openalex.org/W2963322354","https://openalex.org/W2964105799","https://openalex.org/W2979473749","https://openalex.org/W3101762025","https://openalex.org/W3101990100","https://openalex.org/W3104950855","https://openalex.org/W3105340263","https://openalex.org/W3148325197","https://openalex.org/W4205551177","https://openalex.org/W4235713725","https://openalex.org/W4245256025","https://openalex.org/W4250519137","https://openalex.org/W4250955649","https://openalex.org/W6638389366","https://openalex.org/W6724289339"],"related_works":["https://openalex.org/W2384787007","https://openalex.org/W2737338842","https://openalex.org/W2244779222","https://openalex.org/W2984862312","https://openalex.org/W2809017213","https://openalex.org/W2067878805","https://openalex.org/W1973065909","https://openalex.org/W3201815179","https://openalex.org/W2053479107","https://openalex.org/W2158173952"],"abstract_inverted_index":{"We":[0,108],"study":[1],"the":[2,10,15,29,71,81,89,106,129,142,166,170,185,206,212,222,245,248,287,291,305,314,323],"support":[3,246],"recovery":[4,68,113,135],"problem":[5,114],"for":[6,218,278,299,304,337],"compressed":[7,47],"sensing,":[8],"where":[9,88,261,313],"goal":[11,187],"is":[12,44,77,209,263],"to":[13,345],"reconstruct":[14],"sparsity":[16,207],"pattern":[17],"of":[18,54,128,224,244,247,289,326,348],"a":[19,45,51,66,97,161,176,232,346],"high-dimensional":[20],"K-sparse":[21,151],"signal":[22,152,213,250,307],"x":[23],"\u2208":[24],"\u211dN,":[25],"as":[26,28],"well":[27],"corresponding":[30],"sparse":[31,57,90,171,249,271,292],"coefficients,":[32],"from":[33,197],"low-dimensional":[34],"linear":[35],"measurements":[36,158,195],"with":[37,61,115,160,200],"and":[38,65,122,134,178,221,257],"without":[39],"noise.":[40],"Our":[41],"key":[42],"contribution":[43],"new":[46,52],"sensing":[48],"framework":[49,76,125,146,182,328],"through":[50,84],"family":[53],"carefully":[55],"designed":[56,78],"measurement":[58,63,72,130,198],"matrices":[59],"associated":[60],"minimal":[62],"costs":[64],"low-complexity":[67],"algorithm.":[69],"Specifically,":[70,137],"matrix":[73,199],"in":[74,96,118,126,141,153,175,188,211],"our":[75,124,145,181,235,327],"based":[79],"on":[80],"well-crafted":[82],"sparsification":[83],"capacity-approaching":[85],"sparse-graph":[86],"codes,":[87],"coefficients":[91,172,227,293],"can":[92,147,183,237,274,317,330],"be":[93,318],"recovered":[94,270],"efficiently":[95],"few":[98],"iterations":[99],"by":[100,231,297],"performing":[101],"simple":[102],"error":[103,163,277],"decoding":[104,117],"over":[105],"observations.":[107],"formally":[109],"connect":[110],"this":[111],"general":[112],"sparsegraph":[116],"packet":[119],"communication":[120],"systems":[121],"analyze":[123],"terms":[127],"cost,":[131],"computational":[132],"complexity,":[133],"performance.":[136],"we":[138,273],"show":[139],"that":[140,329],"noiseless":[143],"setting,":[144,168],"recover":[148,238],"any":[149],"arbitrary":[150],"O(K)":[154],"time":[155,189],"using":[156,192,251],"2K":[157],"asymptotically":[159],"vanishing":[162],"probability.":[164],"In":[165,284],"noisy":[167],"when":[169],"take":[173],"values":[174],"finite":[177],"quantized":[179],"alphabet,":[180],"achieve":[184,275],"same":[186],"O(K":[190,193,252,258],"log(N/K))":[191,194,255],"obtained":[196],"elements":[201],"{-1,":[202],"0,":[203],"1}.":[204],"When":[205],"K":[208,215],"sub-linear":[210],"dimension":[214],"=":[216],"O(N\u03b4)":[217],"some":[219,300],"0\u03b4)":[220],"magnitudes":[223,288],"all":[225,290],"thesparse":[226],"are":[228,294,343],"bounded":[229,296],"below":[230],"positive":[233],"constant,":[234],"algorithm":[236],"an":[239,264,279],"arbitrarily":[240,265,280,319],"large":[241],"(1-":[242],"p)-fraction":[243],"log(N/K)":[253],"log":[254],"measurements,":[256],"log3(N/K))":[259],"run-time,":[260],"r":[262],"small":[266,281],"constant.":[267],"For":[268],"each":[269],"coefficient,":[272],"O(\u2208)":[276],"constant":[282,301,315],"E.":[283],"addition,":[285],"if":[286],"upper":[295],"O(Kc)":[298],"c1recovery":[302],"guarantee":[303],"estimated":[306],"x\u0302:":[308],"\u2225x\u0302":[309],"-":[310],"x\u22251\u2264":[311],"\u03ba\u2225x\u22251,":[312],"\u03ba":[316],"small.":[320],"This":[321],"offers":[322],"desired":[324],"scalability":[325],"potentially":[331],"enable":[332],"real-time":[333],"or":[334],"near-realtime":[335],"processing":[336],"massive":[338],"datasets":[339],"featuring":[340],"sparsity,":[341],"which":[342],"relevant":[344],"multitude":[347],"practical":[349],"applications.":[350]},"counts_by_year":[{"year":2023,"cited_by_count":4},{"year":2022,"cited_by_count":4},{"year":2021,"cited_by_count":3},{"year":2020,"cited_by_count":4},{"year":2019,"cited_by_count":1},{"year":2016,"cited_by_count":1}],"updated_date":"2026-07-29T09:40:50.615796","created_date":"2025-10-10T00:00:00"}
