{"id":"https://openalex.org/W2963307262","doi":"https://doi.org/10.1109/allerton.2017.8262790","title":"Learning mixtures of sparse linear regressions using sparse graph codes","display_name":"Learning mixtures of sparse linear regressions using sparse graph codes","publication_year":2017,"publication_date":"2017-10-01","ids":{"openalex":"https://openalex.org/W2963307262","doi":"https://doi.org/10.1109/allerton.2017.8262790","mag":"2963307262"},"language":"en","primary_location":{"id":"doi:10.1109/allerton.2017.8262790","is_oa":false,"landing_page_url":"https://doi.org/10.1109/allerton.2017.8262790","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2017 55th 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/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":true,"raw_author_name":"Dong Yin","raw_affiliation_strings":["Department of Electrical Engineering and Computer Sciences, UC Berkeley"],"affiliations":[{"raw_affiliation_string":"Department of Electrical Engineering and Computer Sciences, UC Berkeley","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 Electrical and Computer Engineering, UC Santa Barbara"],"affiliations":[{"raw_affiliation_string":"Department of Electrical and Computer Engineering, UC Santa Barbara","institution_ids":["https://openalex.org/I154570441"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5060774236","display_name":"Yudong Chen","orcid":"https://orcid.org/0000-0002-6416-5635"},"institutions":[{"id":"https://openalex.org/I205783295","display_name":"Cornell University","ror":"https://ror.org/05bnh6r87","country_code":"US","type":"education","lineage":["https://openalex.org/I205783295"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Yudong Chen","raw_affiliation_strings":["School of Operations Research and Information Engineering, Cornell University"],"affiliations":[{"raw_affiliation_string":"School of Operations Research and Information Engineering, Cornell University","institution_ids":["https://openalex.org/I205783295"]}]},{"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 Electrical Engineering and Computer Sciences, UC Berkeley"],"affiliations":[{"raw_affiliation_string":"Department of Electrical Engineering and Computer Sciences, UC Berkeley","institution_ids":["https://openalex.org/I95457486"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5001139821"],"corresponding_institution_ids":["https://openalex.org/I95457486"],"apc_list":null,"apc_paid":null,"fwci":0.1063,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.50820334,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":94},"biblio":{"volume":null,"issue":null,"first_page":"588","last_page":"595"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10207","display_name":"Advanced biosensing and bioanalysis techniques","score":0.9943000078201294,"subfield":{"id":"https://openalex.org/subfields/1312","display_name":"Molecular Biology"},"field":{"id":"https://openalex.org/fields/13","display_name":"Biochemistry, Genetics and Molecular Biology"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}},"topics":[{"id":"https://openalex.org/T10207","display_name":"Advanced biosensing and bioanalysis techniques","score":0.9943000078201294,"subfield":{"id":"https://openalex.org/subfields/1312","display_name":"Molecular Biology"},"field":{"id":"https://openalex.org/fields/13","display_name":"Biochemistry, Genetics and Molecular Biology"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}},{"id":"https://openalex.org/T12072","display_name":"Machine Learning and Algorithms","score":0.9911999702453613,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"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/T11321","display_name":"Error Correcting Code Techniques","score":0.9749000072479248,"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/computer-science","display_name":"Computer science","score":0.4200117290019989},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.38711118698120117},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.3601958155632019}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.4200117290019989},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.38711118698120117},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.3601958155632019}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/allerton.2017.8262790","is_oa":false,"landing_page_url":"https://doi.org/10.1109/allerton.2017.8262790","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2017 55th Annual Allerton Conference on Communication, Control, and Computing (Allerton)","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":45,"referenced_works":["https://openalex.org/W1503100111","https://openalex.org/W1870871427","https://openalex.org/W1920167102","https://openalex.org/W1974648697","https://openalex.org/W2041823554","https://openalex.org/W2080575882","https://openalex.org/W2093463916","https://openalex.org/W2096725512","https://openalex.org/W2098288588","https://openalex.org/W2099020507","https://openalex.org/W2104733578","https://openalex.org/W2115220575","https://openalex.org/W2124428910","https://openalex.org/W2127771408","https://openalex.org/W2128765501","https://openalex.org/W2138142480","https://openalex.org/W2138967244","https://openalex.org/W2149734713","https://openalex.org/W2150498905","https://openalex.org/W2152326788","https://openalex.org/W2169732368","https://openalex.org/W2171035569","https://openalex.org/W2171406132","https://openalex.org/W2187927593","https://openalex.org/W2340619382","https://openalex.org/W2407380148","https://openalex.org/W2518479542","https://openalex.org/W2588111195","https://openalex.org/W2607151738","https://openalex.org/W2962737134","https://openalex.org/W2963002486","https://openalex.org/W2963768921","https://openalex.org/W2964105799","https://openalex.org/W2964207716","https://openalex.org/W3101651037","https://openalex.org/W4239719188","https://openalex.org/W4243066824","https://openalex.org/W6639303850","https://openalex.org/W6674319481","https://openalex.org/W6678489871","https://openalex.org/W6678848472","https://openalex.org/W6680662047","https://openalex.org/W6685075181","https://openalex.org/W6687037121","https://openalex.org/W6713806399"],"related_works":["https://openalex.org/W4391375266","https://openalex.org/W2748952813","https://openalex.org/W2051487156","https://openalex.org/W2073681303","https://openalex.org/W2390279801","https://openalex.org/W2358668433","https://openalex.org/W4396701345","https://openalex.org/W2376932109","https://openalex.org/W2001405890","https://openalex.org/W4396696052"],"abstract_inverted_index":{"In":[0,222],"this":[1],"paper,":[2],"we":[3],"consider":[4],"the":[5,46,79,83,95,116,121,130,135,146,149,166,199,209,219],"mixture":[6,167,230],"of":[7,36,71,78,119,133,205,224,231,258],"sparse":[8,30,80,136,181],"linear":[9,41],"regressions":[10,233],"model.":[11],"Let":[12],"\u03b2":[13,18,60,138],"<sup":[14,19,24,57,61,139],"xmlns:mml=\"http://www.w3.org/1998/Math/MathML\"":[15,20,25,50,55,58,62,67,87,125,140,174],"xmlns:xlink=\"http://www.w3.org/1999/xlink\">(1)</sup>":[16],",...,":[17],"xmlns:xlink=\"http://www.w3.org/1999/xlink\">(L)</sup>":[21],"\u03f5":[22],"C":[23],"xmlns:xlink=\"http://www.w3.org/1999/xlink\">n</sup>":[26],"be":[27],"L":[28],"unknown":[29],"parameter":[31,96,194],"vectors":[32,81,97,137,171],"with":[33,82,99,234,255],"a":[34,160,229],"total":[35],"K":[37,241],"non-zero":[38],"coefficients.":[39],"Noisy":[40],"measurements":[42],"are":[43],"obtained":[44],"in":[45,208,218],"form":[47],"y":[48],"<sub":[49,54,66,86,124,173],"xmlns:xlink=\"http://www.w3.org/1999/xlink\">i</sub>":[51,56,68,88,175],"=":[52,237,242],"x":[53,172],"xmlns:xlink=\"http://www.w3.org/1999/xlink\">H</sup>":[59],"xmlns:xlink=\"http://www.w3.org/1999/xlink\">(\u2113i)</sup>":[63],"+":[64],"w":[65],",":[69],"each":[70],"which":[72,164],"is":[73,92,246],"generated":[74],"randomly":[75],"from":[76,180],"one":[77,111,223],"label":[84],"\u2113":[85,123],"unknown.":[89],"The":[90,196],"goal":[91],"to":[93,113,145,227],"estimate":[94],"efficiently":[98],"low":[100],"sample":[101,201,260],"and":[102,155,193,202,212,239],"computational":[103],"costs.":[104],"This":[105],"problem":[106,118,132,147],"presents":[107],"significant":[108],"challenges":[109],"as":[110,127,129],"needs":[112],"simultaneously":[114],"solve":[115],"demixing":[117,192],"recovering":[120,134],"labels":[122],"xmlns:xlink=\"http://www.w3.org/1999/xlink\">1</sub>":[126],"well":[128],"estimation":[131],"xmlns:xlink=\"http://www.w3.org/1999/xlink\">(\u2113)</sup>":[141],".":[142],"Our":[143,184],"solution":[144],"leverages":[148],"connection":[150],"between":[151],"modern":[152],"coding":[153],"theory":[154],"statistical":[156],"inference.":[157],"We":[158],"introduce":[159],"new":[161],"algorithm,":[162,254],"Mixed-Coloring,":[163],"samples":[165],"strategically":[168],"using":[169],"query":[170],"constructed":[176],"based":[177],"on":[178],"ideas":[179],"graph":[182],"codes.":[183],"novel":[185],"code":[186],"design":[187],"allows":[188],"for":[189],"both":[190],"efficient":[191],"estimation.":[195],"algorithm":[197,245],"achieves":[198],"order-optimal":[200],"time":[203],"complexities":[204,217],"\u0398":[206,214],"(K)":[207],"noiseless":[210],"setting,":[211],"near-optimal":[213],"(K":[215],"polylog(n))":[216],"noisy":[220],"setting.":[221],"our":[225,244],"experiments,":[226],"recover":[228],"two":[232],"dimension":[235],"n":[236],"500":[238],"sparsity":[240],"50,":[243],"more":[247],"than":[248,252],"300":[249],"times":[250],"faster":[251],"EM":[253],"about":[256],"1/3":[257],"its":[259],"cost.":[261]},"counts_by_year":[{"year":2019,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}