{"id":"https://openalex.org/W1972727637","doi":"https://doi.org/10.1109/isit.2014.6875353","title":"The Gaussian rate-distortion function of sparse regression codes with optimal encoding","display_name":"The Gaussian rate-distortion function of sparse regression codes with optimal encoding","publication_year":2014,"publication_date":"2014-06-01","ids":{"openalex":"https://openalex.org/W1972727637","doi":"https://doi.org/10.1109/isit.2014.6875353","mag":"1972727637"},"language":"en","primary_location":{"id":"doi:10.1109/isit.2014.6875353","is_oa":false,"landing_page_url":"https://doi.org/10.1109/isit.2014.6875353","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2014 IEEE International Symposium on Information Theory","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/A5081409970","display_name":"Ramji Venkataramanan","orcid":"https://orcid.org/0000-0001-7915-5432"},"institutions":[{"id":"https://openalex.org/I241749","display_name":"University of Cambridge","ror":"https://ror.org/013meh722","country_code":"GB","type":"education","lineage":["https://openalex.org/I241749"]}],"countries":["GB"],"is_corresponding":true,"raw_author_name":"Ramji Venkataramanan","raw_affiliation_strings":["University of Cambridge, UK","University of Cambridge, Cambridge, UK"],"affiliations":[{"raw_affiliation_string":"University of Cambridge, UK","institution_ids":["https://openalex.org/I241749"]},{"raw_affiliation_string":"University of Cambridge, Cambridge, UK","institution_ids":["https://openalex.org/I241749"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5072765803","display_name":"Sekhar Tatikonda","orcid":"https://orcid.org/0000-0002-8956-6208"},"institutions":[{"id":"https://openalex.org/I32971472","display_name":"Yale University","ror":"https://ror.org/03v76x132","country_code":"US","type":"education","lineage":["https://openalex.org/I32971472"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Sekhar Tatikonda","raw_affiliation_strings":["Yale University, USA","\u2020Yale University, New Haven, CT, USA"],"affiliations":[{"raw_affiliation_string":"Yale University, USA","institution_ids":["https://openalex.org/I32971472"]},{"raw_affiliation_string":"\u2020Yale University, New Haven, CT, USA","institution_ids":["https://openalex.org/I32971472"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5081409970"],"corresponding_institution_ids":["https://openalex.org/I241749"],"apc_list":null,"apc_paid":null,"fwci":0.6308,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":{"value":0.66976951,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":94,"max":96},"biblio":{"volume":"58","issue":null,"first_page":"2844","last_page":"2848"},"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/T10964","display_name":"Wireless Communication Security Techniques","score":0.9994000196456909,"subfield":{"id":"https://openalex.org/subfields/2208","display_name":"Electrical and Electronic Engineering"},"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/T12879","display_name":"Distributed Sensor Networks and Detection Algorithms","score":0.9988999962806702,"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/distortion","display_name":"Distortion (music)","score":0.7186155915260315},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.633317232131958},{"id":"https://openalex.org/keywords/encoding","display_name":"Encoding (memory)","score":0.6146187782287598},{"id":"https://openalex.org/keywords/gaussian","display_name":"Gaussian","score":0.6099743843078613},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.6021223664283752},{"id":"https://openalex.org/keywords/function","display_name":"Function (biology)","score":0.5114892721176147},{"id":"https://openalex.org/keywords/moment","display_name":"Moment (physics)","score":0.49730995297431946},{"id":"https://openalex.org/keywords/rate\u2013distortion-theory","display_name":"Rate\u2013distortion theory","score":0.4832099676132202},{"id":"https://openalex.org/keywords/random-variable","display_name":"Random variable","score":0.4711001515388489},{"id":"https://openalex.org/keywords/moment-generating-function","display_name":"Moment-generating function","score":0.4651172459125519},{"id":"https://openalex.org/keywords/matrix","display_name":"Matrix (chemical analysis)","score":0.41068726778030396},{"id":"https://openalex.org/keywords/applied-mathematics","display_name":"Applied mathematics","score":0.3523869514465332},{"id":"https://openalex.org/keywords/discrete-mathematics","display_name":"Discrete mathematics","score":0.3443683087825775},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.3154931366443634},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.3113401532173157},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.191647469997406},{"id":"https://openalex.org/keywords/data-compression","display_name":"Data compression","score":0.09843069314956665},{"id":"https://openalex.org/keywords/telecommunications","display_name":"Telecommunications","score":0.08247709274291992}],"concepts":[{"id":"https://openalex.org/C126780896","wikidata":"https://www.wikidata.org/wiki/Q899871","display_name":"Distortion (music)","level":4,"score":0.7186155915260315},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.633317232131958},{"id":"https://openalex.org/C125411270","wikidata":"https://www.wikidata.org/wiki/Q18653","display_name":"Encoding (memory)","level":2,"score":0.6146187782287598},{"id":"https://openalex.org/C163716315","wikidata":"https://www.wikidata.org/wiki/Q901177","display_name":"Gaussian","level":2,"score":0.6099743843078613},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.6021223664283752},{"id":"https://openalex.org/C14036430","wikidata":"https://www.wikidata.org/wiki/Q3736076","display_name":"Function (biology)","level":2,"score":0.5114892721176147},{"id":"https://openalex.org/C179254644","wikidata":"https://www.wikidata.org/wiki/Q13222844","display_name":"Moment (physics)","level":2,"score":0.49730995297431946},{"id":"https://openalex.org/C64185310","wikidata":"https://www.wikidata.org/wiki/Q843483","display_name":"Rate\u2013distortion theory","level":3,"score":0.4832099676132202},{"id":"https://openalex.org/C122123141","wikidata":"https://www.wikidata.org/wiki/Q176623","display_name":"Random variable","level":2,"score":0.4711001515388489},{"id":"https://openalex.org/C101796028","wikidata":"https://www.wikidata.org/wiki/Q535587","display_name":"Moment-generating function","level":3,"score":0.4651172459125519},{"id":"https://openalex.org/C106487976","wikidata":"https://www.wikidata.org/wiki/Q685816","display_name":"Matrix (chemical analysis)","level":2,"score":0.41068726778030396},{"id":"https://openalex.org/C28826006","wikidata":"https://www.wikidata.org/wiki/Q33521","display_name":"Applied mathematics","level":1,"score":0.3523869514465332},{"id":"https://openalex.org/C118615104","wikidata":"https://www.wikidata.org/wiki/Q121416","display_name":"Discrete mathematics","level":1,"score":0.3443683087825775},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.3154931366443634},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.3113401532173157},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.191647469997406},{"id":"https://openalex.org/C78548338","wikidata":"https://www.wikidata.org/wiki/Q2493","display_name":"Data compression","level":2,"score":0.09843069314956665},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.08247709274291992},{"id":"https://openalex.org/C74650414","wikidata":"https://www.wikidata.org/wiki/Q11397","display_name":"Classical mechanics","level":1,"score":0.0},{"id":"https://openalex.org/C192562407","wikidata":"https://www.wikidata.org/wiki/Q228736","display_name":"Materials science","level":0,"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/C2776257435","wikidata":"https://www.wikidata.org/wiki/Q1576430","display_name":"Bandwidth (computing)","level":2,"score":0.0},{"id":"https://openalex.org/C194257627","wikidata":"https://www.wikidata.org/wiki/Q211554","display_name":"Amplifier","level":3,"score":0.0},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"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/C78458016","wikidata":"https://www.wikidata.org/wiki/Q840400","display_name":"Evolutionary biology","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/isit.2014.6875353","is_oa":false,"landing_page_url":"https://doi.org/10.1109/isit.2014.6875353","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2014 IEEE International Symposium on Information Theory","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.4300000071525574,"id":"https://metadata.un.org/sdg/16","display_name":"Peace, Justice and strong institutions"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":11,"referenced_works":["https://openalex.org/W1610636547","https://openalex.org/W1806595454","https://openalex.org/W1972727637","https://openalex.org/W2039957496","https://openalex.org/W2106648739","https://openalex.org/W2166171880","https://openalex.org/W2166347904","https://openalex.org/W2478722229","https://openalex.org/W3109965631","https://openalex.org/W6675910762","https://openalex.org/W6786485656"],"related_works":["https://openalex.org/W4224311898","https://openalex.org/W2140857733","https://openalex.org/W2997019937","https://openalex.org/W2625143318","https://openalex.org/W2018697056","https://openalex.org/W2096321176","https://openalex.org/W2985832736","https://openalex.org/W2771826620","https://openalex.org/W2373670823","https://openalex.org/W2328588095"],"abstract_inverted_index":{"We":[0,90],"study":[1],"the":[2,10,38,69,93,96,99],"rate-distortion":[3,40],"performance":[4],"of":[5,15,17,19,98],"Sparse":[6],"Regression":[7],"Codes":[8],"where":[9],"codewords":[11],"are":[12],"linear":[13],"combinations":[14],"subsets":[16],"columns":[18],"a":[20,49,61,73,79,110],"design":[21],"matrix.":[22],"It":[23],"is":[24,66,84,116],"shown":[25],"that":[26,54,78,114],"with":[27,87],"minimum-distance":[28],"encoding":[29],"and":[30,107],"squared":[31],"error":[32],"distortion,":[33],"these":[34],"codes":[35],"achieve":[36],"R*(D),":[37],"Shannon":[39],"function":[41],"for":[42,58,104,118],"an":[43],"i.i.d.":[44],"Gaussian":[45],"source.":[46],"This":[47],"completes":[48],"previous":[50],"result":[51],"which":[52],"showed":[53],"R*(D)":[55,115],"was":[56],"achievable":[57,117],"distortions":[59],"below":[60],"certain":[62],"threshold.":[63],"The":[64],"proof":[65],"based":[67],"on":[68],"second":[70,101],"moment":[71,102],"method,":[72],"popular":[74],"technique":[75],"to":[76,112],"show":[77,113],"non-negative":[80],"random":[81],"variable":[82],"X":[83],"strictly":[85],"positive":[86],"high":[88],"probability.":[89],"first":[91],"identify":[92],"reason":[94],"behind":[95],"failure":[97],"vanilla":[100],"method":[103],"this":[105],"problem,":[106],"then":[108],"introduce":[109],"refinement":[111],"all":[119],"distortions.":[120]},"counts_by_year":[{"year":2014,"cited_by_count":2}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
