{"id":"https://openalex.org/W2147542713","doi":"https://doi.org/10.1109/allerton.2010.5707100","title":"A general framework for high-dimensional estimation in the presence of incoherence","display_name":"A general framework for high-dimensional estimation in the presence of incoherence","publication_year":2010,"publication_date":"2010-09-01","ids":{"openalex":"https://openalex.org/W2147542713","doi":"https://doi.org/10.1109/allerton.2010.5707100","mag":"2147542713"},"language":"en","primary_location":{"id":"doi:10.1109/allerton.2010.5707100","is_oa":false,"landing_page_url":"https://doi.org/10.1109/allerton.2010.5707100","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2010 48th Annual Allerton Conference on Communication, Control, and Computing (Allerton)","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/A5100416078","display_name":"Yuxin Chen","orcid":"https://orcid.org/0000-0001-9256-5815"},"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":"Yuxin Chen","raw_affiliation_strings":["Department of Electrical Engineering, University of Stanford, USA"],"affiliations":[{"raw_affiliation_string":"Department of Electrical Engineering, University of Stanford, USA","institution_ids":["https://openalex.org/I97018004"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5110619770","display_name":"Sujay Sanghavi","orcid":null},"institutions":[{"id":"https://openalex.org/I86519309","display_name":"The University of Texas at Austin","ror":"https://ror.org/00hj54h04","country_code":"US","type":"education","lineage":["https://openalex.org/I86519309"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Sujay Sanghavi","raw_affiliation_strings":["Department of Electrical and Computer Engineering, University of Technology, Austin, TX, USA"],"affiliations":[{"raw_affiliation_string":"Department of Electrical and Computer Engineering, University of Technology, Austin, TX, USA","institution_ids":["https://openalex.org/I86519309"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5100416078"],"corresponding_institution_ids":["https://openalex.org/I97018004"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":3,"citation_normalized_percentile":{"value":0.18716715,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":94},"biblio":{"volume":null,"issue":null,"first_page":"1570","last_page":"1576"},"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/T10688","display_name":"Image and Signal Denoising Methods","score":0.9993000030517578,"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"}},{"id":"https://openalex.org/T11447","display_name":"Blind Source Separation Techniques","score":0.998199999332428,"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/estimation","display_name":"Estimation","score":0.6635969877243042},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5692353844642639},{"id":"https://openalex.org/keywords/systems-engineering","display_name":"Systems engineering","score":0.14582404494285583},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.11894279718399048}],"concepts":[{"id":"https://openalex.org/C96250715","wikidata":"https://www.wikidata.org/wiki/Q965330","display_name":"Estimation","level":2,"score":0.6635969877243042},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5692353844642639},{"id":"https://openalex.org/C201995342","wikidata":"https://www.wikidata.org/wiki/Q682496","display_name":"Systems engineering","level":1,"score":0.14582404494285583},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.11894279718399048}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/allerton.2010.5707100","is_oa":false,"landing_page_url":"https://doi.org/10.1109/allerton.2010.5707100","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2010 48th Annual Allerton Conference on Communication, Control, and Computing (Allerton)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Peace, Justice and strong institutions","id":"https://metadata.un.org/sdg/16","score":0.7699999809265137}],"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":34,"referenced_works":["https://openalex.org/W1480312878","https://openalex.org/W1573301526","https://openalex.org/W1966995619","https://openalex.org/W2000157792","https://openalex.org/W2056042427","https://openalex.org/W2065180801","https://openalex.org/W2099641086","https://openalex.org/W2118550318","https://openalex.org/W2125536150","https://openalex.org/W2127271355","https://openalex.org/W2127300249","https://openalex.org/W2129131372","https://openalex.org/W2134332047","https://openalex.org/W2144730813","https://openalex.org/W2145096794","https://openalex.org/W2145962650","https://openalex.org/W2147276092","https://openalex.org/W2151825876","https://openalex.org/W2159268085","https://openalex.org/W2163107063","https://openalex.org/W2167839759","https://openalex.org/W2244441628","https://openalex.org/W2296616510","https://openalex.org/W2611328865","https://openalex.org/W2951443864","https://openalex.org/W2951927428","https://openalex.org/W2963322354","https://openalex.org/W3104624268","https://openalex.org/W4250955649","https://openalex.org/W6640723650","https://openalex.org/W6678640197","https://openalex.org/W6682550672","https://openalex.org/W6690618759","https://openalex.org/W6764481259"],"related_works":["https://openalex.org/W4391375266","https://openalex.org/W2748952813","https://openalex.org/W2390279801","https://openalex.org/W2358668433","https://openalex.org/W4396701345","https://openalex.org/W2376932109","https://openalex.org/W2001405890","https://openalex.org/W4396696052","https://openalex.org/W4402327032","https://openalex.org/W2382290278"],"abstract_inverted_index":{"High-dimensional":[0],"statistical":[1],"inference":[2],"requires":[3],"the":[4,34,43,77,114,137,187,206,229],"recovery/estimation":[5],"of":[6,10,18,23,84,149,178,180,199,208,210,231,242],"a":[7,13,91,101,157,203,211,238],"large":[8],"number":[9,17],"parameters":[11],"from":[12],"possibly":[14],"much":[15],"smaller":[16],"samples.":[19],"A":[20],"growing":[21],"body":[22],"recent":[24,188],"work":[25,98,184],"has":[26,88],"established":[27],"that":[28,104,129,164,172],"this":[29,51,97],"is":[30,45,202],"possible":[31],"provided":[32],"(a)":[33,151],"signal":[35],"possesses":[36],"an":[37],"appropriate":[38,152],"low-dimensional":[39],"structure,":[40],"and":[41,61,86,124,126,140,155],"(b)":[42,156],"sampling":[44],"\u201cincoherent\u201d,":[46],"i.e.":[47],"does":[48],"not":[49,218],"suppress":[50],"structure.":[52],"Popular":[53],"structural":[54],"assumptions":[55],"include":[56,65],"sparsity,":[57],"block-sparsity,":[58],"low-rank":[59],"etc.,":[60],"popular":[62],"recovery":[63,134],"approaches":[64,73],"regularization":[66],"via":[67],"convex":[68,153,191],"penalties,":[69],"alternating":[70],"projections,":[71],"greedy":[72],"etc.":[74],"However,":[75],"in":[76,113,133,136,142,196,205,220],"existing":[78,170],"literature,":[79],"analysis":[80],"for":[81,122,145,190],"each":[82,179],"combination":[83],"structure":[85,123],"method":[87],"proceeded":[89],"on":[90,186],"case":[92,94,230],"by":[93,193],"basis.":[95],"In":[96],"we":[99,118,165,223,236],"provide":[100,119],"unified":[102],"framework":[103,189,227],"broadly":[105],"characterizes":[106],"when":[107],"incoherence":[108,130,243],"will":[109],"enable":[110],"consistent":[111],"estimation":[112],"high-dimensional":[115],"setting.":[116],"Specifically,":[117],"general":[120],"definitions":[121],"incoherence,":[125,209],"then":[127],"establish":[128],"guarantees":[131],"success":[132],"(exactly":[135],"noiseless":[138],"case,":[139],"approximately":[141],"noisy":[143],"case)":[144],"two":[146],"broad":[147],"classes":[148],"methods:":[150],"regularization,":[154],"new":[158,239],"algorithm":[159],"-":[160,163,244],"Generalized":[161],"Projections":[162],"propose.":[166],"We":[167],"identify":[168],"several":[169],"results":[171,201],"are":[173],"recovered":[174],"as":[175],"special":[176],"cases":[177],"our":[181,200,226],"results.":[182],"Our":[183],"builds":[185],"regularizers":[192],"Negahban":[194],"et.al.;":[195],"particular":[197],"one":[198],"characterization,":[204],"presence":[207],"crucial":[212],"constant":[213],"they":[214],"define":[215,237],"but":[216],"do":[217],"evaluate":[219],"general.":[221],"Finally,":[222],"also":[224],"extend":[225],"to":[228],"multiple":[232],"superimposed":[233],"structures,":[234],"where":[235],"inter-structure":[240],"notions":[241],"Restricted":[245],"Orthogonality":[246],"Property.":[247]},"counts_by_year":[{"year":2020,"cited_by_count":1},{"year":2016,"cited_by_count":1},{"year":2015,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
