{"id":"https://openalex.org/W4387682283","doi":"https://doi.org/10.1109/tcomm.2023.3324658","title":"MCMC Sampling-Based Randomized Likelihood Decoding for Sparse Recovery","display_name":"MCMC Sampling-Based Randomized Likelihood Decoding for Sparse Recovery","publication_year":2023,"publication_date":"2023-10-16","ids":{"openalex":"https://openalex.org/W4387682283","doi":"https://doi.org/10.1109/tcomm.2023.3324658"},"language":"en","primary_location":{"id":"doi:10.1109/tcomm.2023.3324658","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tcomm.2023.3324658","pdf_url":null,"source":{"id":"https://openalex.org/S196647941","display_name":"IEEE Transactions on Communications","issn_l":"0090-6778","issn":["0090-6778","1558-0857"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310316002","host_organization_name":"IEEE Communications Society","host_organization_lineage":["https://openalex.org/P4310316002","https://openalex.org/P4310319808"],"host_organization_lineage_names":["IEEE Communications Society","Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Communications","raw_type":"journal-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/A5006027074","display_name":"Yoonseong Kang","orcid":"https://orcid.org/0000-0002-3382-2911"},"institutions":[{"id":"https://openalex.org/I157485424","display_name":"Korea Advanced Institute of Science and Technology","ror":"https://ror.org/05apxxy63","country_code":"KR","type":"education","lineage":["https://openalex.org/I157485424"]}],"countries":["KR"],"is_corresponding":true,"raw_author_name":"Yoonseong Kang","raw_affiliation_strings":["School of Electrical Engineering, Korea Advanced Institute of Science and Technology (KAIST), Daejeon, South Korea","School of Electrical Engineering, Korea Advanced Institute of Science and Technology (KAIST), Daejeon, Korea"],"raw_orcid":"https://orcid.org/0000-0002-3382-2911","affiliations":[{"raw_affiliation_string":"School of Electrical Engineering, Korea Advanced Institute of Science and Technology (KAIST), Daejeon, South Korea","institution_ids":["https://openalex.org/I157485424"]},{"raw_affiliation_string":"School of Electrical Engineering, Korea Advanced Institute of Science and Technology (KAIST), Daejeon, Korea","institution_ids":["https://openalex.org/I157485424"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5035102148","display_name":"Wan Choi","orcid":"https://orcid.org/0000-0003-3930-7088"},"institutions":[{"id":"https://openalex.org/I139264467","display_name":"Seoul National University","ror":"https://ror.org/04h9pn542","country_code":"KR","type":"education","lineage":["https://openalex.org/I139264467"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Wan Choi","raw_affiliation_strings":["Department of Electrical and Computer Engineering and the Institute of New Media and Communications, Seoul National University (SNU), Seoul, South Korea","Department of Electrical and Computer Engineering and the Institute of New Media and Communications, Seoul National University (SNU), Seoul, Korea"],"raw_orcid":"https://orcid.org/0000-0003-3930-7088","affiliations":[{"raw_affiliation_string":"Department of Electrical and Computer Engineering and the Institute of New Media and Communications, Seoul National University (SNU), Seoul, South Korea","institution_ids":["https://openalex.org/I139264467"]},{"raw_affiliation_string":"Department of Electrical and Computer Engineering and the Institute of New Media and Communications, Seoul National University (SNU), Seoul, Korea","institution_ids":["https://openalex.org/I139264467"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5006027074"],"corresponding_institution_ids":["https://openalex.org/I157485424"],"apc_list":null,"apc_paid":null,"fwci":0.2071,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.48131531,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":94},"biblio":{"volume":"72","issue":"1","first_page":"465","last_page":"479"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10500","display_name":"Sparse and Compressive Sensing Techniques","score":0.9998000264167786,"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":0.9998000264167786,"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":0.9998000264167786,"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/T10688","display_name":"Image and Signal Denoising Methods","score":0.9864000082015991,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/markov-chain-monte-carlo","display_name":"Markov chain Monte Carlo","score":0.7481054663658142},{"id":"https://openalex.org/keywords/compressed-sensing","display_name":"Compressed sensing","score":0.6252855062484741},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.6124860048294067},{"id":"https://openalex.org/keywords/decoding-methods","display_name":"Decoding methods","score":0.5933701992034912},{"id":"https://openalex.org/keywords/sampling","display_name":"Sampling (signal processing)","score":0.5687002539634705},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5395184755325317},{"id":"https://openalex.org/keywords/gibbs-sampling","display_name":"Gibbs sampling","score":0.45731469988822937},{"id":"https://openalex.org/keywords/importance-sampling","display_name":"Importance sampling","score":0.4454774856567383},{"id":"https://openalex.org/keywords/signal","display_name":"SIGNAL (programming language)","score":0.44105905294418335},{"id":"https://openalex.org/keywords/monte-carlo-method","display_name":"Monte Carlo method","score":0.3468095660209656},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.30979788303375244},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.2363700568675995},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.22700512409210205},{"id":"https://openalex.org/keywords/bayesian-probability","display_name":"Bayesian probability","score":0.09959018230438232},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.08362236618995667}],"concepts":[{"id":"https://openalex.org/C111350023","wikidata":"https://www.wikidata.org/wiki/Q1191869","display_name":"Markov chain Monte Carlo","level":3,"score":0.7481054663658142},{"id":"https://openalex.org/C124851039","wikidata":"https://www.wikidata.org/wiki/Q2665459","display_name":"Compressed sensing","level":2,"score":0.6252855062484741},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.6124860048294067},{"id":"https://openalex.org/C57273362","wikidata":"https://www.wikidata.org/wiki/Q576722","display_name":"Decoding methods","level":2,"score":0.5933701992034912},{"id":"https://openalex.org/C140779682","wikidata":"https://www.wikidata.org/wiki/Q210868","display_name":"Sampling (signal processing)","level":3,"score":0.5687002539634705},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5395184755325317},{"id":"https://openalex.org/C158424031","wikidata":"https://www.wikidata.org/wiki/Q1191905","display_name":"Gibbs sampling","level":3,"score":0.45731469988822937},{"id":"https://openalex.org/C52740198","wikidata":"https://www.wikidata.org/wiki/Q1539564","display_name":"Importance sampling","level":3,"score":0.4454774856567383},{"id":"https://openalex.org/C2779843651","wikidata":"https://www.wikidata.org/wiki/Q7390335","display_name":"SIGNAL (programming language)","level":2,"score":0.44105905294418335},{"id":"https://openalex.org/C19499675","wikidata":"https://www.wikidata.org/wiki/Q232207","display_name":"Monte Carlo method","level":2,"score":0.3468095660209656},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.30979788303375244},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.2363700568675995},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.22700512409210205},{"id":"https://openalex.org/C107673813","wikidata":"https://www.wikidata.org/wiki/Q812534","display_name":"Bayesian probability","level":2,"score":0.09959018230438232},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.08362236618995667},{"id":"https://openalex.org/C106131492","wikidata":"https://www.wikidata.org/wiki/Q3072260","display_name":"Filter (signal processing)","level":2,"score":0.0},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tcomm.2023.3324658","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tcomm.2023.3324658","pdf_url":null,"source":{"id":"https://openalex.org/S196647941","display_name":"IEEE Transactions on Communications","issn_l":"0090-6778","issn":["0090-6778","1558-0857"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310316002","host_organization_name":"IEEE Communications Society","host_organization_lineage":["https://openalex.org/P4310316002","https://openalex.org/P4310319808"],"host_organization_lineage_names":["IEEE Communications Society","Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Communications","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G2617297419","display_name":null,"funder_award_id":"RS-2023-00220985","funder_id":"https://openalex.org/F4320322120","funder_display_name":"National Research Foundation of Korea"},{"id":"https://openalex.org/G7644865607","display_name":null,"funder_award_id":"2021R1A2C2003230","funder_id":"https://openalex.org/F4320322120","funder_display_name":"National Research Foundation of Korea"},{"id":"https://openalex.org/G8818249485","display_name":null,"funder_award_id":"RS-2023-00220985","funder_id":"https://openalex.org/F4320322030","funder_display_name":"Ministry of Science, ICT and Future Planning"},{"id":"https://openalex.org/G8902105557","display_name":null,"funder_award_id":"2021R1A2C2003230","funder_id":"https://openalex.org/F4320322030","funder_display_name":"Ministry of Science, ICT and Future Planning"}],"funders":[{"id":"https://openalex.org/F4320322030","display_name":"Ministry of Science, ICT and Future Planning","ror":"https://ror.org/032e49973"},{"id":"https://openalex.org/F4320322120","display_name":"National Research Foundation of Korea","ror":"https://ror.org/013aysd81"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":43,"referenced_works":["https://openalex.org/W143004564","https://openalex.org/W749681720","https://openalex.org/W1968525509","https://openalex.org/W1986931325","https://openalex.org/W2035929826","https://openalex.org/W2053521124","https://openalex.org/W2054692642","https://openalex.org/W2065513175","https://openalex.org/W2071284784","https://openalex.org/W2075337042","https://openalex.org/W2078804453","https://openalex.org/W2101517901","https://openalex.org/W2111953900","https://openalex.org/W2127271355","https://openalex.org/W2135859872","https://openalex.org/W2139831589","https://openalex.org/W2163107063","https://openalex.org/W2264830470","https://openalex.org/W2289917018","https://openalex.org/W2295803031","https://openalex.org/W2495931889","https://openalex.org/W2773666931","https://openalex.org/W2808769356","https://openalex.org/W2894913314","https://openalex.org/W2905459276","https://openalex.org/W2909069749","https://openalex.org/W2912014066","https://openalex.org/W2912280348","https://openalex.org/W2962959174","https://openalex.org/W2963322354","https://openalex.org/W2963550795","https://openalex.org/W3031418291","https://openalex.org/W3043682498","https://openalex.org/W3147919432","https://openalex.org/W4206097460","https://openalex.org/W4212863985","https://openalex.org/W4233022137","https://openalex.org/W4250955649","https://openalex.org/W4252713891","https://openalex.org/W4295016751","https://openalex.org/W4300263211","https://openalex.org/W4312258136","https://openalex.org/W6675139043"],"related_works":["https://openalex.org/W3125971950","https://openalex.org/W1580681286","https://openalex.org/W2116700007","https://openalex.org/W2175355783","https://openalex.org/W1579866848","https://openalex.org/W3139342328","https://openalex.org/W2622204791","https://openalex.org/W1546022168","https://openalex.org/W2066716418","https://openalex.org/W2905524938"],"abstract_inverted_index":{"We":[0,127],"investigate":[1],"whether":[2],"randomized":[3],"likelihood":[4],"(RL)":[5],"decoding":[6,39],"based":[7,117],"on":[8,118],"sampling":[9,83,115,141],"techniques":[10],"can":[11,164],"completely":[12],"replace":[13],"the":[14,43,76,80,92,109,113,119,123,130,137,145,150,160,181,186],"compressed":[15],"sensing":[16],"(CS)":[17],"process":[18,69,103],"for":[19,75],"sparse":[20,46,77,110],"recovery.":[21],"For":[22],"a":[23,29,68,87,102,193],"Gaussian":[24],"signal":[25,78,111,146,182,195],"model,":[26],"we":[27],"propose":[28],"novel":[30],"iterative":[31,52,139],"Markov":[32],"chain":[33],"Monte":[34],"Carlo":[35],"(MCMC)":[36],"sampling-based":[37],"RL":[38],"method":[40,116],"tailored":[41],"to":[42,191],"attributes":[44],"of":[45,70,104,108,136],"recovery,":[47],"termed":[48],"MCMC-RLD-SR.":[49],"The":[50,64,98],"proposed":[51,131,138,151,161,187],"MCMC-RLD-SR":[53,162],"algorithm":[54,132,163,188],"incorporates":[55],"two":[56],"stages,":[57],"i.e.,":[58],"rough":[59,65,124],"estimation":[60,66,100,125],"and":[61,143,155],"fine":[62,99],"estimation.":[63],"is":[67,101,183,189],"figuring":[71],"out":[72],"support":[73,120],"candidates":[74,121],"via":[79],"Metropolis-Hastings":[81],"(MH)":[82],"method,":[84],"which":[85],"prevents":[86],"nonconvergence":[88],"issue":[89],"inherent":[90],"in":[91],"CS":[93,167,176],"problem":[94],"when":[95,180],"applying":[96],"sampling.":[97],"acquiring":[105],"an":[106],"estimate":[107],"through":[112],"Gibbs":[114],"from":[122],"stage.":[126],"prove":[128],"that":[129,159],"converges":[133],"by":[134,149],"favor":[135],"two-stage":[140],"structure,":[142],"analyze":[144],"recovery":[147,196],"error":[148],"algorithm.":[152],"Our":[153],"analysis":[154],"simulation":[156],"results":[157],"show":[158],"effectively":[165],"solve":[166],"problems":[168],"with":[169],"much":[170],"less":[171],"computational":[172],"complexity":[173],"than":[174],"conventional":[175],"algorithms.":[177],"Furthermore,":[178],"even":[179],"not":[184],"sparse,":[185],"shown":[190],"achieve":[192],"reliable":[194],"performance.":[197]},"counts_by_year":[{"year":2024,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
