{"id":"https://openalex.org/W2566924527","doi":"https://doi.org/10.1137/16m1108340","title":"Efficient Bayesian Computation by Proximal Markov Chain Monte Carlo: When Langevin Meets Moreau","display_name":"Efficient Bayesian Computation by Proximal Markov Chain Monte Carlo: When Langevin Meets Moreau","publication_year":2018,"publication_date":"2018-01-01","ids":{"openalex":"https://openalex.org/W2566924527","doi":"https://doi.org/10.1137/16m1108340","mag":"2566924527"},"language":"en","primary_location":{"id":"doi:10.1137/16m1108340","is_oa":false,"landing_page_url":"https://doi.org/10.1137/16m1108340","pdf_url":null,"source":{"id":"https://openalex.org/S152600803","display_name":"SIAM Journal on Imaging Sciences","issn_l":"1936-4954","issn":["1936-4954"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320508","host_organization_name":"Society for Industrial and Applied Mathematics","host_organization_lineage":["https://openalex.org/P4310320508"],"host_organization_lineage_names":["Society for Industrial and Applied Mathematics"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"SIAM Journal on Imaging Sciences","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/A5036096413","display_name":"Alain Durmus","orcid":"https://orcid.org/0000-0002-2086-8611"},"institutions":[{"id":"https://openalex.org/I4210150889","display_name":"Center for MathematicaL studies and their Applications","ror":"https://ror.org/05pabaz56","country_code":"FR","type":"facility","lineage":["https://openalex.org/I11559806","https://openalex.org/I1294671590","https://openalex.org/I277688954","https://openalex.org/I4210141950","https://openalex.org/I4210150889"]},{"id":"https://openalex.org/I4210165912","display_name":"Laboratoire Traitement et Communication de l\u2019Information","ror":"https://ror.org/057er4c39","country_code":"FR","type":"facility","lineage":["https://openalex.org/I12356871","https://openalex.org/I205703379","https://openalex.org/I4210145102","https://openalex.org/I4210165912"]}],"countries":["FR"],"is_corresponding":false,"raw_author_name":"Alain Durmus","raw_affiliation_strings":["Centre de Math\u00e9matiques et de Leurs Applications","Laboratoire Traitement et Communication de l'Information"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Centre de Math\u00e9matiques et de Leurs Applications","institution_ids":["https://openalex.org/I4210150889"]},{"raw_affiliation_string":"Laboratoire Traitement et Communication de l'Information","institution_ids":["https://openalex.org/I4210165912"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101398712","display_name":"\u00c9ric Moulines","orcid":"https://orcid.org/0000-0002-2058-0693"},"institutions":[{"id":"https://openalex.org/I142476485","display_name":"\u00c9cole Polytechnique","ror":"https://ror.org/05hy3tk52","country_code":"FR","type":"education","lineage":["https://openalex.org/I142476485","https://openalex.org/I4210145102"]},{"id":"https://openalex.org/I4210095810","display_name":"Laboratoire Analyse et Mod\u00e9lisation pour la Biologie et l'Environnement","ror":"https://ror.org/00wwxk695","country_code":"FR","type":"facility","lineage":["https://openalex.org/I1294671590","https://openalex.org/I1294671590","https://openalex.org/I2738703131","https://openalex.org/I277688954","https://openalex.org/I4210095810","https://openalex.org/I4210128300","https://openalex.org/I4210142324","https://openalex.org/I88467170"]},{"id":"https://openalex.org/I4210107641","display_name":"Centre de Math\u00e9matiques Appliqu\u00e9es de l'\u00c9cole polytechnique","ror":"https://ror.org/012e1xn46","country_code":"FR","type":"facility","lineage":["https://openalex.org/I1294671590","https://openalex.org/I1294671590","https://openalex.org/I1326498283","https://openalex.org/I142476485","https://openalex.org/I4210107641","https://openalex.org/I4210141950","https://openalex.org/I4210145102"]},{"id":"https://openalex.org/I4210165912","display_name":"Laboratoire Traitement et Communication de l\u2019Information","ror":"https://ror.org/057er4c39","country_code":"FR","type":"facility","lineage":["https://openalex.org/I12356871","https://openalex.org/I205703379","https://openalex.org/I4210145102","https://openalex.org/I4210165912"]}],"countries":["FR"],"is_corresponding":false,"raw_author_name":"\u00c9ric Moulines","raw_affiliation_strings":["Centre de Math\u00e9matiques Appliqu\u00e9es - Ecole Polytechnique","Laboratoire Traitement et Communication de l'Information","Mod\u00e9lisation en pharmacologie de population"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Centre de Math\u00e9matiques Appliqu\u00e9es - Ecole Polytechnique","institution_ids":["https://openalex.org/I142476485","https://openalex.org/I4210107641"]},{"raw_affiliation_string":"Laboratoire Traitement et Communication de l'Information","institution_ids":["https://openalex.org/I4210165912"]},{"raw_affiliation_string":"Mod\u00e9lisation en pharmacologie de population","institution_ids":["https://openalex.org/I4210095810"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5082169271","display_name":"Marcelo Pereyra","orcid":"https://orcid.org/0000-0001-6438-6772"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Marcelo Pereyra","raw_affiliation_strings":["School of Mathematics [Bristol]"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Mathematics [Bristol]","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":10.5453,"has_fulltext":false,"cited_by_count":162,"citation_normalized_percentile":{"value":0.9886479,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":90,"max":100},"biblio":{"volume":"11","issue":"1","first_page":"473","last_page":"506"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10522","display_name":"Medical Imaging Techniques and Applications","score":0.9998000264167786,"subfield":{"id":"https://openalex.org/subfields/2741","display_name":"Radiology, Nuclear Medicine and Imaging"},"field":{"id":"https://openalex.org/fields/27","display_name":"Medicine"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}},"topics":[{"id":"https://openalex.org/T10522","display_name":"Medical Imaging Techniques and Applications","score":0.9998000264167786,"subfield":{"id":"https://openalex.org/subfields/2741","display_name":"Radiology, Nuclear Medicine and Imaging"},"field":{"id":"https://openalex.org/fields/27","display_name":"Medicine"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}},{"id":"https://openalex.org/T10500","display_name":"Sparse and Compressive Sensing Techniques","score":0.9994999766349792,"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/T10136","display_name":"Statistical Methods and Inference","score":0.9990000128746033,"subfield":{"id":"https://openalex.org/subfields/2613","display_name":"Statistics and Probability"},"field":{"id":"https://openalex.org/fields/26","display_name":"Mathematics"},"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":0.7767112851142883},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5334024429321289},{"id":"https://openalex.org/keywords/mathematical-optimization","display_name":"Mathematical optimization","score":0.5070929527282715},{"id":"https://openalex.org/keywords/bayesian-inference","display_name":"Bayesian inference","score":0.49910759925842285},{"id":"https://openalex.org/keywords/monte-carlo-method","display_name":"Monte Carlo method","score":0.48945820331573486},{"id":"https://openalex.org/keywords/markov-chain","display_name":"Markov chain","score":0.47789084911346436},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.4644705355167389},{"id":"https://openalex.org/keywords/bayesian-probability","display_name":"Bayesian probability","score":0.4249390661716461},{"id":"https://openalex.org/keywords/prior-probability","display_name":"Prior probability","score":0.4240148365497589},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.35783594846725464},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.28103530406951904},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.20923209190368652},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.07817849516868591}],"concepts":[{"id":"https://openalex.org/C111350023","wikidata":"https://www.wikidata.org/wiki/Q1191869","display_name":"Markov chain Monte Carlo","level":3,"score":0.7767112851142883},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5334024429321289},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.5070929527282715},{"id":"https://openalex.org/C160234255","wikidata":"https://www.wikidata.org/wiki/Q812535","display_name":"Bayesian inference","level":3,"score":0.49910759925842285},{"id":"https://openalex.org/C19499675","wikidata":"https://www.wikidata.org/wiki/Q232207","display_name":"Monte Carlo method","level":2,"score":0.48945820331573486},{"id":"https://openalex.org/C98763669","wikidata":"https://www.wikidata.org/wiki/Q176645","display_name":"Markov chain","level":2,"score":0.47789084911346436},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.4644705355167389},{"id":"https://openalex.org/C107673813","wikidata":"https://www.wikidata.org/wiki/Q812534","display_name":"Bayesian probability","level":2,"score":0.4249390661716461},{"id":"https://openalex.org/C177769412","wikidata":"https://www.wikidata.org/wiki/Q278090","display_name":"Prior probability","level":3,"score":0.4240148365497589},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.35783594846725464},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.28103530406951904},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.20923209190368652},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.07817849516868591}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1137/16m1108340","is_oa":false,"landing_page_url":"https://doi.org/10.1137/16m1108340","pdf_url":null,"source":{"id":"https://openalex.org/S152600803","display_name":"SIAM Journal on Imaging Sciences","issn_l":"1936-4954","issn":["1936-4954"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320508","host_organization_name":"Society for Industrial and Applied Mathematics","host_organization_lineage":["https://openalex.org/P4310320508"],"host_organization_lineage_names":["Society for Industrial and Applied Mathematics"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"SIAM Journal on Imaging Sciences","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320311518","display_name":"Heriot-Watt University","ror":"https://ror.org/04mghma93"},{"id":"https://openalex.org/F4320320360","display_name":"University of Bristol","ror":"https://ror.org/0524sp257"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":30,"referenced_works":["https://openalex.org/W639587122","https://openalex.org/W1555683961","https://openalex.org/W1558572410","https://openalex.org/W1774344329","https://openalex.org/W1971159979","https://openalex.org/W1982652137","https://openalex.org/W1983452151","https://openalex.org/W1984145374","https://openalex.org/W1990075812","https://openalex.org/W1997763492","https://openalex.org/W1999897837","https://openalex.org/W2003268963","https://openalex.org/W2005089986","https://openalex.org/W2014666811","https://openalex.org/W2031299022","https://openalex.org/W2039091494","https://openalex.org/W2042621213","https://openalex.org/W2043709234","https://openalex.org/W2050841740","https://openalex.org/W2057291289","https://openalex.org/W2058005980","https://openalex.org/W2092264912","https://openalex.org/W2101675075","https://openalex.org/W2123031198","https://openalex.org/W2292392078","https://openalex.org/W2963270586","https://openalex.org/W3102541574","https://openalex.org/W3104267706","https://openalex.org/W3148325197","https://openalex.org/W4250955649"],"related_works":["https://openalex.org/W2562263695","https://openalex.org/W2135187896","https://openalex.org/W2147201983","https://openalex.org/W2015518264","https://openalex.org/W2795035211","https://openalex.org/W2160108762","https://openalex.org/W2017034551","https://openalex.org/W3087071515","https://openalex.org/W4283077537","https://openalex.org/W2999603699"],"abstract_inverted_index":{"Modern":[0],"imaging":[1,12,104],"methods":[2],"rely":[3],"strongly":[4],"on":[5,110,183],"Bayesian":[6,17,61,86,214],"inference":[7],"techniques":[8,63],"to":[9,27,40,56,84,128,138,141,147,149,196,217],"solve":[10],"challenging":[11,213],"problems.":[13],"Currently,":[14],"the":[15,143,167,184,226],"predominant":[16],"computation":[18,62,87],"approach":[19],"is":[20,54,101,108,145,190],"convex":[21,120],"optimization,":[22],"which":[23],"scales":[24],"very":[25],"efficiently":[26,140],"high-dimensional":[28,89],"image":[29,47,197],"models":[30,90,99,150],"and":[31,76,94,125,172,180,199,204,222],"delivers":[32],"accurate":[33],"point":[34],"estimation":[35],"results.":[36],"However,":[37],"in":[38,103,225],"order":[39],"perform":[41,85],"more":[42,58],"complex":[43],"analyses,":[44],"for":[45,88],"example,":[46],"uncertainty":[48,218],"quantification":[49],"or":[50],"model":[51,223],"selection,":[52],"it":[53],"necessary":[55],"use":[57],"computationally":[59],"intensive":[60],"such":[64],"as":[65],"Markov":[66,79,130],"chain":[67,80],"Monte":[68,81],"Carlo":[69,82],"methods.":[70],"This":[71],"paper":[72],"presents":[73],"a":[74,96,111,162,210],"new":[75],"highly":[77],"efficient":[78],"methodology":[83,107,189],"that":[91,100,116,151],"are":[92,152],"log-concave":[93],"nonsmooth,":[95],"class":[97],"of":[98,166,212,228],"central":[102],"sciences.":[105],"The":[106,187],"based":[109],"regularized":[112],"unadjusted":[113],"Langevin":[114],"algorithm":[115],"exploits":[117],"tools":[118],"from":[119],"analysis,":[121],"namely,":[122],"Moreau--Yoshida":[123],"envelopes":[124],"proximal":[126,157],"operators,":[127],"construct":[129],"chains":[131],"with":[132,176,192,202],"favorable":[133],"convergence":[134,174,185],"properties.":[135],"In":[136],"addition":[137],"scaling":[139],"high-dimensions,":[142],"method":[144],"straightforward":[146],"apply":[148],"currently":[153],"solved":[154],"by":[155],"using":[156],"optimization":[158],"algorithms.":[159],"We":[160],"provide":[161],"detailed":[163],"theoretical":[164],"analysis":[165],"proposed":[168,188],"methodology,":[169],"including":[170],"asymptotic":[171],"nonasymptotic":[173],"results":[175],"easily":[177],"verifiable":[178],"conditions,":[179],"explicit":[181],"bounds":[182],"rates.":[186],"demonstrated":[191],"four":[193],"experiments":[194],"related":[195,216],"deconvolution":[198],"tomographic":[200],"reconstruction":[201],"total-variation":[203],"$\\ell_1$":[205],"priors,":[206],"where":[207],"we":[208],"conduct":[209],"range":[211],"analyses":[215],"quantification,":[219],"hypothesis":[220],"testing,":[221],"selection":[224],"absence":[227],"ground":[229],"truth.":[230]},"counts_by_year":[{"year":2026,"cited_by_count":9},{"year":2025,"cited_by_count":19},{"year":2024,"cited_by_count":23},{"year":2023,"cited_by_count":26},{"year":2022,"cited_by_count":18},{"year":2021,"cited_by_count":14},{"year":2020,"cited_by_count":17},{"year":2019,"cited_by_count":27},{"year":2018,"cited_by_count":8},{"year":2017,"cited_by_count":1}],"updated_date":"2026-07-31T08:31:51.225901","created_date":"2025-10-10T00:00:00"}
