{"id":"https://openalex.org/W2137050212","doi":"https://doi.org/10.1109/cdc.2002.1184883","title":"Discrete optimization, SPSA and Markov chain Monte Carlo methods","display_name":"Discrete optimization, SPSA and Markov chain Monte Carlo methods","publication_year":2003,"publication_date":"2003-08-27","ids":{"openalex":"https://openalex.org/W2137050212","doi":"https://doi.org/10.1109/cdc.2002.1184883","mag":"2137050212"},"language":"en","primary_location":{"id":"doi:10.1109/cdc.2002.1184883","is_oa":false,"landing_page_url":"https://doi.org/10.1109/cdc.2002.1184883","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 41st IEEE Conference on Decision and Control, 2002.","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/A5103169746","display_name":"L\u00e1szl\u00f3 Gerencs\u00e9r","orcid":"https://orcid.org/0000-0003-4239-7950"},"institutions":[{"id":"https://openalex.org/I7597260","display_name":"Hungarian Academy of Sciences","ror":"https://ror.org/02ks8qq67","country_code":"HU","type":"funder","lineage":["https://openalex.org/I7597260"]},{"id":"https://openalex.org/I4210117195","display_name":"Institute for Computer Science and Control","ror":"https://ror.org/0249v7n71","country_code":"HU","type":"facility","lineage":["https://openalex.org/I4210117195","https://openalex.org/I7597260"]}],"countries":["HU"],"is_corresponding":true,"raw_author_name":"L. Gerencser","raw_affiliation_strings":["Computer and Automation Institute of the Hungarian Academy of Sciences, Budapest, Hungary","Comput. & Autom. Inst., Hungarian Acad. of Sci., Budapest, Hungary"],"affiliations":[{"raw_affiliation_string":"Computer and Automation Institute of the Hungarian Academy of Sciences, Budapest, Hungary","institution_ids":["https://openalex.org/I7597260"]},{"raw_affiliation_string":"Comput. & Autom. Inst., Hungarian Acad. of Sci., Budapest, Hungary","institution_ids":["https://openalex.org/I4210117195"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5006578922","display_name":"S.D. Hill","orcid":"https://orcid.org/0000-0003-4752-7486"},"institutions":[{"id":"https://openalex.org/I2802946424","display_name":"Johns Hopkins University Applied Physics Laboratory","ror":"https://ror.org/029pp9z10","country_code":"US","type":"facility","lineage":["https://openalex.org/I145311948","https://openalex.org/I2802946424"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"S.D. Hill","raw_affiliation_strings":["Applied Physics Lab., John Hopkins Univ., Laucel, MD","[Applied Physics Laboratory]"],"affiliations":[{"raw_affiliation_string":"Applied Physics Lab., John Hopkins Univ., Laucel, MD","institution_ids":["https://openalex.org/I2802946424"]},{"raw_affiliation_string":"[Applied Physics Laboratory]","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5103169746"],"corresponding_institution_ids":["https://openalex.org/I4210117195","https://openalex.org/I7597260"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.20089142,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"2","issue":null,"first_page":"2346","last_page":"2347"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10363","display_name":"Low-power high-performance VLSI design","score":0.9934999942779541,"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"}},"topics":[{"id":"https://openalex.org/T10363","display_name":"Low-power high-performance VLSI design","score":0.9934999942779541,"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/T11195","display_name":"Simulation Techniques and Applications","score":0.9929999709129333,"subfield":{"id":"https://openalex.org/subfields/1803","display_name":"Management Science and Operations Research"},"field":{"id":"https://openalex.org/fields/18","display_name":"Decision Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},{"id":"https://openalex.org/T11522","display_name":"VLSI and FPGA Design Techniques","score":0.9891999959945679,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/simultaneous-perturbation-stochastic-approximation","display_name":"Simultaneous perturbation stochastic approximation","score":0.9309653043746948},{"id":"https://openalex.org/keywords/markov-chain","display_name":"Markov chain","score":0.6975141763687134},{"id":"https://openalex.org/keywords/mathematical-optimization","display_name":"Mathematical optimization","score":0.6203209161758423},{"id":"https://openalex.org/keywords/monte-carlo-method","display_name":"Monte Carlo method","score":0.6122761368751526},{"id":"https://openalex.org/keywords/markov-chain-monte-carlo","display_name":"Markov chain Monte Carlo","score":0.5819438099861145},{"id":"https://openalex.org/keywords/markov-process","display_name":"Markov process","score":0.5491710305213928},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5161624550819397},{"id":"https://openalex.org/keywords/minification","display_name":"Minification","score":0.4582379162311554},{"id":"https://openalex.org/keywords/markov-chain-mixing-time","display_name":"Markov chain mixing time","score":0.41093334555625916},{"id":"https://openalex.org/keywords/applied-mathematics","display_name":"Applied mathematics","score":0.37004464864730835},{"id":"https://openalex.org/keywords/stochastic-process","display_name":"Stochastic process","score":0.3585978150367737},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.35414227843284607},{"id":"https://openalex.org/keywords/markov-model","display_name":"Markov model","score":0.26384663581848145},{"id":"https://openalex.org/keywords/variable-order-markov-model","display_name":"Variable-order Markov model","score":0.26074427366256714},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.0594172477722168}],"concepts":[{"id":"https://openalex.org/C2779880469","wikidata":"https://www.wikidata.org/wiki/Q17084424","display_name":"Simultaneous perturbation stochastic approximation","level":3,"score":0.9309653043746948},{"id":"https://openalex.org/C98763669","wikidata":"https://www.wikidata.org/wiki/Q176645","display_name":"Markov chain","level":2,"score":0.6975141763687134},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.6203209161758423},{"id":"https://openalex.org/C19499675","wikidata":"https://www.wikidata.org/wiki/Q232207","display_name":"Monte Carlo method","level":2,"score":0.6122761368751526},{"id":"https://openalex.org/C111350023","wikidata":"https://www.wikidata.org/wiki/Q1191869","display_name":"Markov chain Monte Carlo","level":3,"score":0.5819438099861145},{"id":"https://openalex.org/C159886148","wikidata":"https://www.wikidata.org/wiki/Q176645","display_name":"Markov process","level":2,"score":0.5491710305213928},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5161624550819397},{"id":"https://openalex.org/C147764199","wikidata":"https://www.wikidata.org/wiki/Q6865248","display_name":"Minification","level":2,"score":0.4582379162311554},{"id":"https://openalex.org/C97074811","wikidata":"https://www.wikidata.org/wiki/Q6771322","display_name":"Markov chain mixing time","level":5,"score":0.41093334555625916},{"id":"https://openalex.org/C28826006","wikidata":"https://www.wikidata.org/wiki/Q33521","display_name":"Applied mathematics","level":1,"score":0.37004464864730835},{"id":"https://openalex.org/C8272713","wikidata":"https://www.wikidata.org/wiki/Q176737","display_name":"Stochastic process","level":2,"score":0.3585978150367737},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.35414227843284607},{"id":"https://openalex.org/C163836022","wikidata":"https://www.wikidata.org/wiki/Q6771326","display_name":"Markov model","level":3,"score":0.26384663581848145},{"id":"https://openalex.org/C54907487","wikidata":"https://www.wikidata.org/wiki/Q7915688","display_name":"Variable-order Markov model","level":4,"score":0.26074427366256714},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.0594172477722168},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.0}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.1109/cdc.2002.1184883","is_oa":false,"landing_page_url":"https://doi.org/10.1109/cdc.2002.1184883","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 41st IEEE Conference on Decision and Control, 2002.","raw_type":"proceedings-article"},{"id":"pmh:oai:eprints.sztaki.hu:2886","is_oa":false,"landing_page_url":"http://eprints.sztaki.hu/2886/","pdf_url":null,"source":{"id":"https://openalex.org/S4306401907","display_name":"SZTAKI Publication Repository (Hungarian Academy of Sciences)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I7597260","host_organization_name":"Hungarian Academy of Sciences","host_organization_lineage":["https://openalex.org/I7597260"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"Conference or Workshop Item"},{"id":"pmh:oai:eprints.sztaki.hu:3578","is_oa":false,"landing_page_url":"http://eprints.sztaki.hu/3578/","pdf_url":null,"source":{"id":"https://openalex.org/S4306401907","display_name":"SZTAKI Publication Repository (Hungarian Academy of Sciences)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I7597260","host_organization_name":"Hungarian Academy of Sciences","host_organization_lineage":["https://openalex.org/I7597260"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"Conference or Workshop Item"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":22,"referenced_works":["https://openalex.org/W39126767","https://openalex.org/W109881820","https://openalex.org/W145750329","https://openalex.org/W1486153492","https://openalex.org/W1589700598","https://openalex.org/W1985498579","https://openalex.org/W2011236349","https://openalex.org/W2014208555","https://openalex.org/W2022514640","https://openalex.org/W2032431411","https://openalex.org/W2051203581","https://openalex.org/W2056760934","https://openalex.org/W2081076524","https://openalex.org/W2086605818","https://openalex.org/W2108916630","https://openalex.org/W2120465407","https://openalex.org/W2124289529","https://openalex.org/W2138309709","https://openalex.org/W2144908562","https://openalex.org/W2565654137","https://openalex.org/W4239501940","https://openalex.org/W6605963377"],"related_works":["https://openalex.org/W153274026","https://openalex.org/W2113574707","https://openalex.org/W3036209292","https://openalex.org/W2948562640","https://openalex.org/W2076343249","https://openalex.org/W4312246591","https://openalex.org/W2007883828","https://openalex.org/W605100462","https://openalex.org/W4288412324","https://openalex.org/W3125332818"],"abstract_inverted_index":{"The":[0],"minimization":[1],"of":[2,42],"a":[3],"convex":[4],"function":[5],"defined":[6],"over":[7],"the":[8,34,40,43,62],"grid":[9],"Z/sup":[10],"p/":[11],"is":[12,24,46,58,71],"considered.":[13],"A":[14,53,68],"truncated":[15],"fixed":[16],"gain":[17],"simultaneous":[18],"perturbation":[19],"stochastic":[20],"approximation":[21],"(SPSA)":[22],"method":[23,45],"proposed":[25,44],"and":[26,66],"investigated":[27],"in":[28],"combination":[29],"with":[30],"devices":[31],"borrowed":[32],"from":[33],"Markov-chain":[35],"Monte-Carlo":[36],"literature.":[37],"In":[38],"particular,":[39],"performance":[41],"improved":[47],"by":[48],"choosing":[49],"suitable":[50],"acceptance":[51],"probabilities.":[52],"new":[54],"Markovian":[55],"optimization":[56],"problem":[57],"formulated":[59],"to":[60],"get":[61],"best":[63],"rejection":[64],"probability":[65],"gain.":[67],"simulation":[69],"result":[70],"presented.":[72]},"counts_by_year":[],"updated_date":"2026-04-05T17:49:38.594831","created_date":"2025-10-10T00:00:00"}