{"id":"https://openalex.org/W4386918690","doi":"https://doi.org/10.1109/tit.2023.3318152","title":"An Analysis of Transformed Unadjusted Langevin Algorithm for Heavy-Tailed Sampling","display_name":"An Analysis of Transformed Unadjusted Langevin Algorithm for Heavy-Tailed Sampling","publication_year":2023,"publication_date":"2023-09-21","ids":{"openalex":"https://openalex.org/W4386918690","doi":"https://doi.org/10.1109/tit.2023.3318152"},"language":"en","primary_location":{"id":"doi:10.1109/tit.2023.3318152","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tit.2023.3318152","pdf_url":null,"source":{"id":"https://openalex.org/S4502562","display_name":"IEEE Transactions on Information Theory","issn_l":"0018-9448","issn":["0018-9448","1557-9654"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["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 Information Theory","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/A5101610257","display_name":"Ye He","orcid":"https://orcid.org/0000-0003-4686-8449"},"institutions":[{"id":"https://openalex.org/I130701444","display_name":"Georgia Institute of Technology","ror":"https://ror.org/01zkghx44","country_code":"US","type":"education","lineage":["https://openalex.org/I130701444"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Ye He","raw_affiliation_strings":["School of Mathematics, Georgia Institute of Technology, Atlanta, GA, USA"],"raw_orcid":"https://orcid.org/0000-0003-4686-8449","affiliations":[{"raw_affiliation_string":"School of Mathematics, Georgia Institute of Technology, Atlanta, GA, USA","institution_ids":["https://openalex.org/I130701444"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101496710","display_name":"Krishnakumar Balasubramanian","orcid":"https://orcid.org/0000-0001-5271-9314"},"institutions":[{"id":"https://openalex.org/I84218800","display_name":"University of California, Davis","ror":"https://ror.org/05rrcem69","country_code":"US","type":"education","lineage":["https://openalex.org/I84218800"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Krishnakumar Balasubramanian","raw_affiliation_strings":["Department of Statistics, University of California at Davis, Davis, CA, USA"],"raw_orcid":"https://orcid.org/0000-0001-5271-9314","affiliations":[{"raw_affiliation_string":"Department of Statistics, University of California at Davis, Davis, CA, USA","institution_ids":["https://openalex.org/I84218800"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5022491830","display_name":"Murat A. Erdogdu","orcid":"https://orcid.org/0000-0002-4271-8921"},"institutions":[{"id":"https://openalex.org/I185261750","display_name":"University of Toronto","ror":"https://ror.org/03dbr7087","country_code":"CA","type":"education","lineage":["https://openalex.org/I185261750"]}],"countries":["CA"],"is_corresponding":false,"raw_author_name":"Murat A. Erdogdu","raw_affiliation_strings":["Department of Computer Science and the Department of Statistical Sciences, University of Toronto, Toronto, ON, Canada"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Computer Science and the Department of Statistical Sciences, University of Toronto, Toronto, ON, Canada","institution_ids":["https://openalex.org/I185261750"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5101610257"],"corresponding_institution_ids":["https://openalex.org/I130701444"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.13119037,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"70","issue":"1","first_page":"571","last_page":"593"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10500","display_name":"Sparse and Compressive Sensing Techniques","score":0.9984999895095825,"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":0.9984999895095825,"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":0.9940999746322632,"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/T10662","display_name":"Ultrasonics and Acoustic Wave Propagation","score":0.9854999780654907,"subfield":{"id":"https://openalex.org/subfields/2211","display_name":"Mechanics of Materials"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.5689874887466431},{"id":"https://openalex.org/keywords/sampling","display_name":"Sampling (signal processing)","score":0.5391237139701843},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.47877514362335205},{"id":"https://openalex.org/keywords/statistical-physics","display_name":"Statistical physics","score":0.4600188136100769},{"id":"https://openalex.org/keywords/langevin-dynamics","display_name":"Langevin dynamics","score":0.43770214915275574},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.37019360065460205},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.357627809047699},{"id":"https://openalex.org/keywords/physics","display_name":"Physics","score":0.28095516562461853},{"id":"https://openalex.org/keywords/telecommunications","display_name":"Telecommunications","score":0.13530758023262024},{"id":"https://openalex.org/keywords/detector","display_name":"Detector","score":0.09970346093177795}],"concepts":[{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.5689874887466431},{"id":"https://openalex.org/C140779682","wikidata":"https://www.wikidata.org/wiki/Q210868","display_name":"Sampling (signal processing)","level":3,"score":0.5391237139701843},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.47877514362335205},{"id":"https://openalex.org/C121864883","wikidata":"https://www.wikidata.org/wiki/Q677916","display_name":"Statistical physics","level":1,"score":0.4600188136100769},{"id":"https://openalex.org/C2780004032","wikidata":"https://www.wikidata.org/wiki/Q6485978","display_name":"Langevin dynamics","level":2,"score":0.43770214915275574},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.37019360065460205},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.357627809047699},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.28095516562461853},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.13530758023262024},{"id":"https://openalex.org/C94915269","wikidata":"https://www.wikidata.org/wiki/Q1834857","display_name":"Detector","level":2,"score":0.09970346093177795}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tit.2023.3318152","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tit.2023.3318152","pdf_url":null,"source":{"id":"https://openalex.org/S4502562","display_name":"IEEE Transactions on Information Theory","issn_l":"0018-9448","issn":["0018-9448","1557-9654"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["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 Information Theory","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.44999998807907104,"id":"https://metadata.un.org/sdg/2","display_name":"Zero hunger"}],"awards":[{"id":"https://openalex.org/G4278930823","display_name":null,"funder_award_id":"DMS-2053918","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"},{"id":"https://openalex.org/G6290966371","display_name":null,"funder_award_id":"2019-06167","funder_id":"https://openalex.org/F4320334593","funder_display_name":"Natural Sciences and Engineering Research Council of Canada"}],"funders":[{"id":"https://openalex.org/F4320306076","display_name":"National Science Foundation","ror":"https://ror.org/021nxhr62"},{"id":"https://openalex.org/F4320309949","display_name":"Canadian Institute for Advanced Research","ror":"https://ror.org/01sdtdd95"},{"id":"https://openalex.org/F4320334593","display_name":"Natural Sciences and Engineering Research Council of Canada","ror":"https://ror.org/01h531d29"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":67,"referenced_works":["https://openalex.org/W133732286","https://openalex.org/W423603040","https://openalex.org/W1579925870","https://openalex.org/W1595487073","https://openalex.org/W1654586045","https://openalex.org/W1891298814","https://openalex.org/W1954227087","https://openalex.org/W1974932891","https://openalex.org/W1983452151","https://openalex.org/W1985988138","https://openalex.org/W1993950701","https://openalex.org/W1995735753","https://openalex.org/W2012175556","https://openalex.org/W2014248834","https://openalex.org/W2094919061","https://openalex.org/W2120198720","https://openalex.org/W2120984640","https://openalex.org/W2222154095","https://openalex.org/W2274043460","https://openalex.org/W2626299902","https://openalex.org/W2776466161","https://openalex.org/W2962676802","https://openalex.org/W2963097534","https://openalex.org/W2963099148","https://openalex.org/W2963363937","https://openalex.org/W2963599479","https://openalex.org/W2978927916","https://openalex.org/W3006455502","https://openalex.org/W3021350626","https://openalex.org/W3042743256","https://openalex.org/W3084824690","https://openalex.org/W3098860869","https://openalex.org/W3099709074","https://openalex.org/W3121345022","https://openalex.org/W4236312485","https://openalex.org/W4297336933","https://openalex.org/W4312072422","https://openalex.org/W4390097923","https://openalex.org/W6737161507","https://openalex.org/W6747702989","https://openalex.org/W6748401826","https://openalex.org/W6751335087","https://openalex.org/W6756192427","https://openalex.org/W6758672607","https://openalex.org/W6762339893","https://openalex.org/W6762994361","https://openalex.org/W6763263031","https://openalex.org/W6763955891","https://openalex.org/W6764200782","https://openalex.org/W6767727847","https://openalex.org/W6770847983","https://openalex.org/W6774069275","https://openalex.org/W6778506729","https://openalex.org/W6779565673","https://openalex.org/W6779815396","https://openalex.org/W6784345087","https://openalex.org/W6785614634","https://openalex.org/W6787421611","https://openalex.org/W6790151294","https://openalex.org/W6801946655","https://openalex.org/W6810641396","https://openalex.org/W6838019429","https://openalex.org/W6846275387","https://openalex.org/W6846542496","https://openalex.org/W6851091572","https://openalex.org/W6853045462","https://openalex.org/W6853413565"],"related_works":["https://openalex.org/W2144266858","https://openalex.org/W4221165290","https://openalex.org/W3105693600","https://openalex.org/W3107697994","https://openalex.org/W3080947604","https://openalex.org/W2973441963","https://openalex.org/W2030944229","https://openalex.org/W2949164535","https://openalex.org/W3103050273","https://openalex.org/W2780885427"],"abstract_inverted_index":{"We":[0,52,78],"analyze":[1],"the":[2,16,25,54,80,106],"oracle":[3,63],"complexity":[4],"of":[5,24,31,57,110],"sampling":[6],"from":[7],"polynomially":[8],"decaying":[9],"heavy-tailed":[10,58,107],"target":[11,26,69],"densities":[12,59,109],"based":[13,93],"on":[14,20,94],"running":[15],"Unadjusted":[17],"Langevin":[18],"Algorithm":[19],"certain":[21,111],"transformed":[22],"versions":[23],"density.":[27],"The":[28],"specific":[29],"class":[30,56],"closed-form":[32],"transformation":[33],"maps":[34],"that":[35],"we":[36],"construct":[37],"are":[38,44],"shown":[39],"to":[40,104],"be":[41,72],"diffeomorphisms,":[42],"and":[43,67,74,85,89],"particularly":[45],"suited":[46],"for":[47,60],"developing":[48],"efficient":[49],"diffusion-based":[50],"samplers.":[51],"characterize":[53,105],"precise":[55],"which":[61],"polynomial-order":[62],"complexities":[64],"(in":[65],"dimension":[66],"inverse":[68],"accuracy)":[70],"could":[71],"obtained,":[73],"provide":[75],"illustrative":[76],"examples.":[77],"highlight":[79],"relationship":[81],"between":[82],"our":[83],"assumptions":[84],"functional":[86],"inequalities":[87],"(super":[88],"weak":[90],"Poincar\u00e9":[91],"inequalities)":[92],"non-local":[95],"Dirichlet":[96],"forms":[97],"defined":[98],"via":[99],"fractional":[100],"Laplacian":[101],"operators,":[102],"used":[103],"equilibrium":[108],"stable-driven":[112],"stochastic":[113],"differential":[114],"equations.":[115]},"counts_by_year":[],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
