{"id":"https://openalex.org/W2020301027","doi":"https://doi.org/10.1145/1806689.1806755","title":"Approximate sparse recovery","display_name":"Approximate sparse recovery","publication_year":2010,"publication_date":"2010-06-05","ids":{"openalex":"https://openalex.org/W2020301027","doi":"https://doi.org/10.1145/1806689.1806755","mag":"2020301027"},"language":"en","primary_location":{"id":"doi:10.1145/1806689.1806755","is_oa":false,"landing_page_url":"https://doi.org/10.1145/1806689.1806755","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the forty-second ACM symposium on Theory of computing","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/A5042502878","display_name":"Anna C. Gilbert","orcid":"https://orcid.org/0000-0002-9627-9274"},"institutions":[{"id":"https://openalex.org/I27837315","display_name":"University of Michigan","ror":"https://ror.org/00jmfr291","country_code":"US","type":"education","lineage":["https://openalex.org/I27837315"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Anna C. Gilbert","raw_affiliation_strings":["University of Michigan, Ann Arbor, MI, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Michigan, Ann Arbor, MI, USA","institution_ids":["https://openalex.org/I27837315"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5090676285","display_name":"Yi Li","orcid":"https://orcid.org/0000-0002-6420-653X"},"institutions":[{"id":"https://openalex.org/I27837315","display_name":"University of Michigan","ror":"https://ror.org/00jmfr291","country_code":"US","type":"education","lineage":["https://openalex.org/I27837315"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Yi Li","raw_affiliation_strings":["University of Michigan, Ann Arbor, MI, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Michigan, Ann Arbor, MI, USA","institution_ids":["https://openalex.org/I27837315"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5049614530","display_name":"Ely Porat","orcid":"https://orcid.org/0000-0001-6912-5766"},"institutions":[{"id":"https://openalex.org/I13955877","display_name":"Bar-Ilan University","ror":"https://ror.org/03kgsv495","country_code":"IL","type":"education","lineage":["https://openalex.org/I13955877"]}],"countries":["IL"],"is_corresponding":false,"raw_author_name":"Ely Porat","raw_affiliation_strings":["Bar Ilan University, Ramat Gan, Israel"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Bar Ilan University, Ramat Gan, Israel","institution_ids":["https://openalex.org/I13955877"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5107196494","display_name":"Martin J. Strauss","orcid":null},"institutions":[{"id":"https://openalex.org/I27837315","display_name":"University of Michigan","ror":"https://ror.org/00jmfr291","country_code":"US","type":"education","lineage":["https://openalex.org/I27837315"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Martin J. Strauss","raw_affiliation_strings":["University of Michigan, Ann Arbor, MI, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Michigan, Ann Arbor, MI, USA","institution_ids":["https://openalex.org/I27837315"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":68,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"475","last_page":"484"},"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/T11447","display_name":"Blind Source Separation Techniques","score":0.9968000054359436,"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/T12879","display_name":"Distributed Sensor Networks and Detection Algorithms","score":0.9955999851226807,"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/decoding-methods","display_name":"Decoding methods","score":0.7967629432678223},{"id":"https://openalex.org/keywords/euclidean-distance","display_name":"Euclidean distance","score":0.578494668006897},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.5238164067268372},{"id":"https://openalex.org/keywords/matrix","display_name":"Matrix (chemical analysis)","score":0.5153467059135437},{"id":"https://openalex.org/keywords/combinatorics","display_name":"Combinatorics","score":0.5111871361732483},{"id":"https://openalex.org/keywords/euclidean-geometry","display_name":"Euclidean geometry","score":0.4959655702114105},{"id":"https://openalex.org/keywords/sparse-matrix","display_name":"Sparse matrix","score":0.4878427982330322},{"id":"https://openalex.org/keywords/matrix-algebra","display_name":"Matrix algebra","score":0.47241368889808655},{"id":"https://openalex.org/keywords/approximation-algorithm","display_name":"Approximation algorithm","score":0.4582407474517822},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.44476187229156494},{"id":"https://openalex.org/keywords/term","display_name":"Term (time)","score":0.41054394841194153},{"id":"https://openalex.org/keywords/discrete-mathematics","display_name":"Discrete mathematics","score":0.36041736602783203},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.3362276256084442},{"id":"https://openalex.org/keywords/physics","display_name":"Physics","score":0.16452261805534363},{"id":"https://openalex.org/keywords/geometry","display_name":"Geometry","score":0.0903468132019043},{"id":"https://openalex.org/keywords/eigenvalues-and-eigenvectors","display_name":"Eigenvalues and eigenvectors","score":0.07156971096992493}],"concepts":[{"id":"https://openalex.org/C57273362","wikidata":"https://www.wikidata.org/wiki/Q576722","display_name":"Decoding methods","level":2,"score":0.7967629432678223},{"id":"https://openalex.org/C120174047","wikidata":"https://www.wikidata.org/wiki/Q847073","display_name":"Euclidean distance","level":2,"score":0.578494668006897},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.5238164067268372},{"id":"https://openalex.org/C106487976","wikidata":"https://www.wikidata.org/wiki/Q685816","display_name":"Matrix (chemical analysis)","level":2,"score":0.5153467059135437},{"id":"https://openalex.org/C114614502","wikidata":"https://www.wikidata.org/wiki/Q76592","display_name":"Combinatorics","level":1,"score":0.5111871361732483},{"id":"https://openalex.org/C129782007","wikidata":"https://www.wikidata.org/wiki/Q162886","display_name":"Euclidean geometry","level":2,"score":0.4959655702114105},{"id":"https://openalex.org/C56372850","wikidata":"https://www.wikidata.org/wiki/Q1050404","display_name":"Sparse matrix","level":3,"score":0.4878427982330322},{"id":"https://openalex.org/C2988995629","wikidata":"https://www.wikidata.org/wiki/Q2915729","display_name":"Matrix algebra","level":3,"score":0.47241368889808655},{"id":"https://openalex.org/C148764684","wikidata":"https://www.wikidata.org/wiki/Q621751","display_name":"Approximation algorithm","level":2,"score":0.4582407474517822},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.44476187229156494},{"id":"https://openalex.org/C61797465","wikidata":"https://www.wikidata.org/wiki/Q1188986","display_name":"Term (time)","level":2,"score":0.41054394841194153},{"id":"https://openalex.org/C118615104","wikidata":"https://www.wikidata.org/wiki/Q121416","display_name":"Discrete mathematics","level":1,"score":0.36041736602783203},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.3362276256084442},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.16452261805534363},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0903468132019043},{"id":"https://openalex.org/C158693339","wikidata":"https://www.wikidata.org/wiki/Q190524","display_name":"Eigenvalues and eigenvectors","level":2,"score":0.07156971096992493},{"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/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/C192562407","wikidata":"https://www.wikidata.org/wiki/Q228736","display_name":"Materials science","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/1806689.1806755","is_oa":false,"landing_page_url":"https://doi.org/10.1145/1806689.1806755","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the forty-second ACM symposium on Theory of computing","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":22,"referenced_works":["https://openalex.org/W1493892051","https://openalex.org/W1531216590","https://openalex.org/W1620362451","https://openalex.org/W1865797552","https://openalex.org/W1974466705","https://openalex.org/W2006506233","https://openalex.org/W2020390700","https://openalex.org/W2080745194","https://openalex.org/W2091904714","https://openalex.org/W2118653712","https://openalex.org/W2120383799","https://openalex.org/W2130979540","https://openalex.org/W2141556672","https://openalex.org/W2162032433","https://openalex.org/W2163258822","https://openalex.org/W2164452299","https://openalex.org/W2167973519","https://openalex.org/W2289917018","https://openalex.org/W2296616510","https://openalex.org/W4250544186","https://openalex.org/W4250955649","https://openalex.org/W6844988796"],"related_works":["https://openalex.org/W2090152127","https://openalex.org/W1965169884","https://openalex.org/W3125580510","https://openalex.org/W2008939113","https://openalex.org/W14679004","https://openalex.org/W1566651525","https://openalex.org/W2977652649","https://openalex.org/W2318206461","https://openalex.org/W37157938","https://openalex.org/W4298154183"],"abstract_inverted_index":{"A":[0],"Euclidean":[1],"approximate":[2],"sparse":[3],"recovery":[4],"system":[5,25,64],"consists":[6],"of":[7,84,89],"parameters":[8],"k,N,":[9],"an":[10],"m-by-N":[11],"measurement":[12],"matrix,":[13],"\u03a6,":[14],"and":[15,86],"a":[16,21],"decoding":[17,91],"algorithm,":[18,92],"D.":[19,93],"Given":[20],"vector,":[22],"x,":[23,62],"the":[24,44,63,73,81,87,90],"approximates":[26],"x":[27],"by":[28],"^x=D(\u03a6":[29],"x),":[30],"which":[31],"must":[32,65],"satisfy":[33],"||x":[34,38],"-":[35,39],"x||2\u2264":[36],"C":[37],"xk||2,":[40],"where":[41],"xk":[42],"denotes":[43],"optimal":[45],"k-term":[46],"approximation":[47],"to":[48],"x.":[49],"(The":[50],"output":[51],"^x":[52],"may":[53],"have":[54],"more":[55],"than":[56],"k":[57],"terms).":[58],"For":[59],"each":[60],"vector":[61],"succeed":[66],"with":[67],"probability":[68],"at":[69],"least":[70],"3/4.":[71],"Among":[72],"goals":[74],"in":[75],"designing":[76],"such":[77],"systems":[78],"are":[79],"minimizing":[80],"number":[82],"m":[83],"measurements":[85],"runtime":[88]},"counts_by_year":[{"year":2022,"cited_by_count":1},{"year":2021,"cited_by_count":1},{"year":2020,"cited_by_count":4},{"year":2018,"cited_by_count":1},{"year":2017,"cited_by_count":1},{"year":2016,"cited_by_count":6},{"year":2015,"cited_by_count":13},{"year":2014,"cited_by_count":5},{"year":2013,"cited_by_count":13},{"year":2012,"cited_by_count":14}],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}
