{"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":"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/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 Electrical Engineering and Computer Sciences, UC Berkeley"],"raw_orcid":null,"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"],"raw_orcid":null,"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"],"raw_orcid":null,"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"],"raw_orcid":null,"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":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.9001,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.81859558,"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":[0,175],"this":[1],"paper,":[2],"we":[3],"consider":[4],"the":[5,34,48,52,60,81,86,91,96,103,106,123,152,162,172],"mixture":[6,124,183],"of":[7,24,40,47,84,94,158,177,184,211],"sparse":[8,18,49,97,134],"linear":[9,29],"regressions":[10,186],"model.":[11],"Let":[12],"\u03b2(1),...,":[13],"\u03b2(L)\u03f5":[14],"Cnbe":[15],"L":[16],"unknown":[17],"parameter":[19,61,147],"vectors":[20,50,62,98,128],"with":[21,51,64,187,208],"a":[22,117,182],"total":[23],"K":[25,194],"non-zero":[26],"coefficients.":[27],"Noisy":[28],"measurements":[30],"are":[31],"obtained":[32],"in":[33,161,171],"form":[35],"yi=":[36],"xiH\u03b2(\u2113i)+":[37],"wi,":[38],"each":[39],"which":[41,121],"is":[42,57,199],"generated":[43],"randomly":[44],"from":[45,133],"one":[46,76,176],"label":[53],"\u2113iunknown.":[54],"The":[55,149],"goal":[56],"to":[58,78,102,180],"estimate":[59],"efficiently":[63],"low":[65],"sample":[66,154,213],"and":[67,112,146,155,165,192],"computational":[68],"costs.":[69],"This":[70],"problem":[71,83,93,104],"presents":[72],"significant":[73],"challenges":[74],"as":[75,90],"needs":[77],"simultaneously":[79],"solve":[80],"demixing":[82,145],"recovering":[85,95],"labels":[87],"\u21131as":[88],"well":[89],"estimation":[92],"\u03b2(\u2113).":[99],"Our":[100,137],"solution":[101],"leverages":[105],"connection":[107],"between":[108],"modern":[109],"coding":[110],"theory":[111],"statistical":[113],"inference.":[114],"We":[115],"introduce":[116],"new":[118],"algorithm,":[119,207],"Mixed-Coloring,":[120],"samples":[122],"strategically":[125],"using":[126],"query":[127],"xiconstructed":[129],"based":[130],"on":[131],"ideas":[132],"graph":[135],"codes.":[136],"novel":[138],"code":[139],"design":[140],"allows":[141],"for":[142],"both":[143],"efficient":[144],"estimation.":[148],"algorithm":[150,198],"achieves":[151],"order-optimal":[153],"time":[156],"complexities":[157,170],"\u0398":[159,167],"(K)":[160],"noiseless":[163],"setting,":[164],"near-optimal":[166],"(K":[168],"polylog(n))":[169],"noisy":[173],"setting.":[174],"our":[178,197],"experiments,":[179],"recover":[181],"two":[185],"dimension":[188],"n":[189],"=":[190,195],"500":[191],"sparsity":[193],"50,":[196],"more":[200],"than":[201,205],"300":[202],"times":[203],"faster":[204],"EM":[206],"about":[209],"1/3":[210],"its":[212],"cost.":[214]},"counts_by_year":[{"year":2019,"cited_by_count":1}],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-10-10T00:00:00"}
