{"id":"https://openalex.org/W2078892792","doi":"https://doi.org/10.1109/icassp.2013.6638276","title":"Using deep stacking network to improve structured compressed sensing with Multiple Measurement Vectors","display_name":"Using deep stacking network to improve structured compressed sensing with Multiple Measurement Vectors","publication_year":2013,"publication_date":"2013-05-01","ids":{"openalex":"https://openalex.org/W2078892792","doi":"https://doi.org/10.1109/icassp.2013.6638276","mag":"2078892792"},"language":"en","primary_location":{"id":"doi:10.1109/icassp.2013.6638276","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icassp.2013.6638276","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2013 IEEE International Conference on Acoustics, Speech and Signal Processing","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/A5033846851","display_name":"Hamid Palangi","orcid":"https://orcid.org/0000-0003-2912-4579"},"institutions":[{"id":"https://openalex.org/I141945490","display_name":"University of British Columbia","ror":"https://ror.org/03rmrcq20","country_code":"CA","type":"education","lineage":["https://openalex.org/I141945490"]}],"countries":["CA"],"is_corresponding":true,"raw_author_name":"Hamid Palangi","raw_affiliation_strings":["Department of Electrical and Computer Engineering, University of British Columbia, Canada","Dept. of Electr. & Comput. Eng., Univ. of British Columbia., Vancouver, BC, Canada"],"affiliations":[{"raw_affiliation_string":"Department of Electrical and Computer Engineering, University of British Columbia, Canada","institution_ids":["https://openalex.org/I141945490"]},{"raw_affiliation_string":"Dept. of Electr. & Comput. Eng., Univ. of British Columbia., Vancouver, BC, Canada","institution_ids":["https://openalex.org/I141945490"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5028143781","display_name":"Rabab Ward","orcid":"https://orcid.org/0000-0002-2471-1902"},"institutions":[{"id":"https://openalex.org/I141945490","display_name":"University of British Columbia","ror":"https://ror.org/03rmrcq20","country_code":"CA","type":"education","lineage":["https://openalex.org/I141945490"]}],"countries":["CA"],"is_corresponding":false,"raw_author_name":"Rabab Ward","raw_affiliation_strings":["Department of Electrical and Computer Engineering, University of British Columbia, Canada","Dept. of Electr. & Comput. Eng., Univ. of British Columbia., Vancouver, BC, Canada"],"affiliations":[{"raw_affiliation_string":"Department of Electrical and Computer Engineering, University of British Columbia, Canada","institution_ids":["https://openalex.org/I141945490"]},{"raw_affiliation_string":"Dept. of Electr. & Comput. Eng., Univ. of British Columbia., Vancouver, BC, Canada","institution_ids":["https://openalex.org/I141945490"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100671324","display_name":"Li Deng","orcid":"https://orcid.org/0000-0002-1014-0790"},"institutions":[{"id":"https://openalex.org/I1290206253","display_name":"Microsoft (United States)","ror":"https://ror.org/00d0nc645","country_code":"US","type":"company","lineage":["https://openalex.org/I1290206253"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Li Deng","raw_affiliation_strings":["Microsoft Research, Redmond, WA, USA","[Microsoft Research,Redmond,WA,USA]"],"affiliations":[{"raw_affiliation_string":"Microsoft Research, Redmond, WA, USA","institution_ids":["https://openalex.org/I1290206253"]},{"raw_affiliation_string":"[Microsoft Research,Redmond,WA,USA]","institution_ids":["https://openalex.org/I1290206253"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5033846851"],"corresponding_institution_ids":["https://openalex.org/I141945490"],"apc_list":null,"apc_paid":null,"fwci":1.7276,"has_fulltext":false,"cited_by_count":18,"citation_normalized_percentile":{"value":0.8399657,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":98},"biblio":{"volume":"1","issue":null,"first_page":"3337","last_page":"3341"},"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/T11447","display_name":"Blind Source Separation Techniques","score":0.9994999766349792,"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/T11739","display_name":"Microwave Imaging and Scattering Analysis","score":0.9984999895095825,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/compressed-sensing","display_name":"Compressed sensing","score":0.8279010057449341},{"id":"https://openalex.org/keywords/stacking","display_name":"Stacking","score":0.7849695682525635},{"id":"https://openalex.org/keywords/row","display_name":"Row","score":0.7195523977279663},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6612218618392944},{"id":"https://openalex.org/keywords/sparse-matrix","display_name":"Sparse matrix","score":0.6585600972175598},{"id":"https://openalex.org/keywords/greedy-algorithm","display_name":"Greedy algorithm","score":0.6055475473403931},{"id":"https://openalex.org/keywords/matrix","display_name":"Matrix (chemical analysis)","score":0.5818621516227722},{"id":"https://openalex.org/keywords/residual","display_name":"Residual","score":0.5645624995231628},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.5514654517173767},{"id":"https://openalex.org/keywords/row-and-column-spaces","display_name":"Row and column spaces","score":0.5253593325614929},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.4653855860233307},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.41161662340164185},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3568331003189087},{"id":"https://openalex.org/keywords/materials-science","display_name":"Materials science","score":0.0996963381767273}],"concepts":[{"id":"https://openalex.org/C124851039","wikidata":"https://www.wikidata.org/wiki/Q2665459","display_name":"Compressed sensing","level":2,"score":0.8279010057449341},{"id":"https://openalex.org/C33347731","wikidata":"https://www.wikidata.org/wiki/Q285210","display_name":"Stacking","level":2,"score":0.7849695682525635},{"id":"https://openalex.org/C135598885","wikidata":"https://www.wikidata.org/wiki/Q1366302","display_name":"Row","level":2,"score":0.7195523977279663},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6612218618392944},{"id":"https://openalex.org/C56372850","wikidata":"https://www.wikidata.org/wiki/Q1050404","display_name":"Sparse matrix","level":3,"score":0.6585600972175598},{"id":"https://openalex.org/C51823790","wikidata":"https://www.wikidata.org/wiki/Q504353","display_name":"Greedy algorithm","level":2,"score":0.6055475473403931},{"id":"https://openalex.org/C106487976","wikidata":"https://www.wikidata.org/wiki/Q685816","display_name":"Matrix (chemical analysis)","level":2,"score":0.5818621516227722},{"id":"https://openalex.org/C155512373","wikidata":"https://www.wikidata.org/wiki/Q287450","display_name":"Residual","level":2,"score":0.5645624995231628},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.5514654517173767},{"id":"https://openalex.org/C104140500","wikidata":"https://www.wikidata.org/wiki/Q2088159","display_name":"Row and column spaces","level":3,"score":0.5253593325614929},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.4653855860233307},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.41161662340164185},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3568331003189087},{"id":"https://openalex.org/C192562407","wikidata":"https://www.wikidata.org/wiki/Q228736","display_name":"Materials science","level":0,"score":0.0996963381767273},{"id":"https://openalex.org/C46141821","wikidata":"https://www.wikidata.org/wiki/Q209402","display_name":"Nuclear magnetic resonance","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/C77088390","wikidata":"https://www.wikidata.org/wiki/Q8513","display_name":"Database","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/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icassp.2013.6638276","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icassp.2013.6638276","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2013 IEEE International Conference on Acoustics, Speech and Signal Processing","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":23,"referenced_works":["https://openalex.org/W1813659000","https://openalex.org/W1974774078","https://openalex.org/W1978516841","https://openalex.org/W1994935303","https://openalex.org/W2002984713","https://openalex.org/W2044762091","https://openalex.org/W2093866254","https://openalex.org/W2100495367","https://openalex.org/W2103955025","https://openalex.org/W2104266187","https://openalex.org/W2112041273","https://openalex.org/W2116064496","https://openalex.org/W2136922672","https://openalex.org/W2149600041","https://openalex.org/W2154332973","https://openalex.org/W2160815625","https://openalex.org/W2164452299","https://openalex.org/W2165225968","https://openalex.org/W2184045248","https://openalex.org/W2296616510","https://openalex.org/W3207342693","https://openalex.org/W4250955649","https://openalex.org/W6638304892"],"related_works":["https://openalex.org/W2313440505","https://openalex.org/W3123744736","https://openalex.org/W2137691148","https://openalex.org/W1505848319","https://openalex.org/W4281399881","https://openalex.org/W2905020035","https://openalex.org/W3166006430","https://openalex.org/W4281971614","https://openalex.org/W2184455175","https://openalex.org/W2186463938"],"abstract_inverted_index":{"We":[0,52],"study":[1],"the":[2,19,23,35,38,59,63,77,94,98,101,104,114,121,133,146,149,155,162],"MMV":[3,69,142,158],"(Multiple":[4],"Measurement":[5],"Vectors)":[6],"compressive":[7,70,159],"sensing":[8,71,160],"setting":[9],"with":[10],"a":[11,82,126],"specific":[12],"sparse":[13,24,64,79,105],"structured":[14,68],"support.":[15],"The":[16,73,88,110],"locations":[17,36],"of":[18,37,48,62,90,136],"non-zero":[20,39],"rows":[21,40,49],"in":[22,66,157],"matrix":[25,65,78,96,106],"are":[26],"not":[27],"known.":[28],"All":[29],"that":[30,34,43],"is":[31,33,93,103],"known":[32],"have":[41],"probabilities":[42],"vary":[44],"from":[45],"one":[46],"group":[47],"to":[50,107,124],"another.":[51],"propose":[53],"two":[54],"novel":[55],"greedy":[56],"algorithms":[57,139],"for":[58,153],"exact":[60],"recovery":[61],"this":[67,91],"problem.":[72],"first":[74],"algorithm":[75,112,147],"models":[76],"structure":[80,156],"using":[81,120,148],"shallow":[83,115],"non-":[84],"linear":[85],"neural":[86,116],"network.":[87,129],"input":[89],"network":[92,117,152],"residual":[95],"after":[97],"prediction":[99,118],"and":[100],"output":[102],"be":[108],"recovered.":[109],"second":[111],"improves":[113],"by":[119],"stacking":[122,128,151],"operation":[123],"form":[125],"deep":[127,150],"Experimental":[130],"evaluation":[131],"demonstrates":[132],"superior":[134],"performance":[135],"both":[137],"new":[138],"over":[140],"existing":[141],"methods.":[143],"Among":[144],"all,":[145],"modelling":[154],"performs":[161],"best.":[163]},"counts_by_year":[{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":2},{"year":2022,"cited_by_count":3},{"year":2021,"cited_by_count":2},{"year":2020,"cited_by_count":4},{"year":2017,"cited_by_count":1},{"year":2016,"cited_by_count":4},{"year":2014,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}