{"id":"https://openalex.org/W4396214970","doi":"https://doi.org/10.1109/tase.2024.3391020","title":"Efficient Learning for Selecting Top-<i>m</i> Context-Dependent Designs","display_name":"Efficient Learning for Selecting Top-<i>m</i> Context-Dependent Designs","publication_year":2024,"publication_date":"2024-04-29","ids":{"openalex":"https://openalex.org/W4396214970","doi":"https://doi.org/10.1109/tase.2024.3391020"},"language":"en","primary_location":{"id":"doi:10.1109/tase.2024.3391020","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tase.2024.3391020","pdf_url":null,"source":{"id":"https://openalex.org/S34881539","display_name":"IEEE Transactions on Automation Science and Engineering","issn_l":"1545-5955","issn":["1545-5955","1558-3783"],"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 Automation Science and Engineering","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/A5082836333","display_name":"Gongbo Zhang","orcid":"https://orcid.org/0000-0002-7517-7666"},"institutions":[{"id":"https://openalex.org/I20231570","display_name":"Peking University","ror":"https://ror.org/02v51f717","country_code":"CN","type":"education","lineage":["https://openalex.org/I20231570"]},{"id":"https://openalex.org/I4210100255","display_name":"Beijing Academy of Artificial Intelligence","ror":"https://ror.org/016a74861","country_code":"CN","type":"other","lineage":["https://openalex.org/I4210100255"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Gongbo Zhang","raw_affiliation_strings":["Guanghua School of Management, PKU-Wuhan Institute for Artificial Intelligence, Peking University, Beijing, China","PKU-Wuhan Institute for Artificial Intelligence, Guanghua School of Management, Peking University, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Guanghua School of Management, PKU-Wuhan Institute for Artificial Intelligence, Peking University, Beijing, China","institution_ids":["https://openalex.org/I4210100255"]},{"raw_affiliation_string":"PKU-Wuhan Institute for Artificial Intelligence, Guanghua School of Management, Peking University, Beijing, China","institution_ids":["https://openalex.org/I4210100255","https://openalex.org/I20231570"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5074278294","display_name":"Sihua Chen","orcid":"https://orcid.org/0000-0002-8640-1520"},"institutions":[{"id":"https://openalex.org/I59649739","display_name":"Jiangxi University of Finance and Economics","ror":"https://ror.org/03efmyj29","country_code":"CN","type":"education","lineage":["https://openalex.org/I59649739"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Sihua Chen","raw_affiliation_strings":["School of Information Management, Jiangxi University of Finance and Economics, Nanchang, China"],"affiliations":[{"raw_affiliation_string":"School of Information Management, Jiangxi University of Finance and Economics, Nanchang, China","institution_ids":["https://openalex.org/I59649739"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5070928752","display_name":"Kuihua Huang","orcid":"https://orcid.org/0000-0001-6365-275X"},"institutions":[{"id":"https://openalex.org/I170215575","display_name":"National University of Defense Technology","ror":"https://ror.org/05d2yfz11","country_code":"CN","type":"education","lineage":["https://openalex.org/I170215575"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Kuihua Huang","raw_affiliation_strings":["College of Systems Engineering, National University of Defense Technology, Changsha, China"],"affiliations":[{"raw_affiliation_string":"College of Systems Engineering, National University of Defense Technology, Changsha, China","institution_ids":["https://openalex.org/I170215575"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5005503619","display_name":"Yijie Peng","orcid":"https://orcid.org/0000-0003-2584-8131"},"institutions":[{"id":"https://openalex.org/I4210100255","display_name":"Beijing Academy of Artificial Intelligence","ror":"https://ror.org/016a74861","country_code":"CN","type":"other","lineage":["https://openalex.org/I4210100255"]},{"id":"https://openalex.org/I20231570","display_name":"Peking University","ror":"https://ror.org/02v51f717","country_code":"CN","type":"education","lineage":["https://openalex.org/I20231570"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yijie Peng","raw_affiliation_strings":["Guanghua School of Management, PKU-Wuhan Institute for Artificial Intelligence, Peking University, Beijing, China","PKU-Wuhan Institute for Artificial Intelligence, Guanghua School of Management, Peking University, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Guanghua School of Management, PKU-Wuhan Institute for Artificial Intelligence, Peking University, Beijing, China","institution_ids":["https://openalex.org/I4210100255"]},{"raw_affiliation_string":"PKU-Wuhan Institute for Artificial Intelligence, Guanghua School of Management, Peking University, Beijing, China","institution_ids":["https://openalex.org/I4210100255","https://openalex.org/I20231570"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5082836333"],"corresponding_institution_ids":["https://openalex.org/I20231570","https://openalex.org/I4210100255"],"apc_list":null,"apc_paid":null,"fwci":2.58,"has_fulltext":false,"cited_by_count":5,"citation_normalized_percentile":{"value":0.8922977,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":98},"biblio":{"volume":"22","issue":null,"first_page":"3210","last_page":"3225"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11195","display_name":"Simulation Techniques and Applications","score":0.9987000226974487,"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"}},"topics":[{"id":"https://openalex.org/T11195","display_name":"Simulation Techniques and Applications","score":0.9987000226974487,"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/T10848","display_name":"Advanced Multi-Objective Optimization Algorithms","score":0.9977999925613403,"subfield":{"id":"https://openalex.org/subfields/1703","display_name":"Computational Theory and Mathematics"},"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/T11798","display_name":"Optimal Experimental Design Methods","score":0.9937000274658203,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/context","display_name":"Context (archaeology)","score":0.6673348546028137},{"id":"https://openalex.org/keywords/selection","display_name":"Selection (genetic algorithm)","score":0.6197221279144287},{"id":"https://openalex.org/keywords/thompson-sampling","display_name":"Thompson sampling","score":0.6132960319519043},{"id":"https://openalex.org/keywords/sampling","display_name":"Sampling (signal processing)","score":0.5995393991470337},{"id":"https://openalex.org/keywords/asymptotically-optimal-algorithm","display_name":"Asymptotically optimal algorithm","score":0.5929062366485596},{"id":"https://openalex.org/keywords/ranking","display_name":"Ranking (information retrieval)","score":0.5743672251701355},{"id":"https://openalex.org/keywords/notation","display_name":"Notation","score":0.5469163656234741},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5088582038879395},{"id":"https://openalex.org/keywords/mathematical-optimization","display_name":"Mathematical optimization","score":0.42378589510917664},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3747093677520752},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.3706960082054138},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.34631651639938354},{"id":"https://openalex.org/keywords/bayesian-probability","display_name":"Bayesian probability","score":0.31579452753067017},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.30817073583602905},{"id":"https://openalex.org/keywords/arithmetic","display_name":"Arithmetic","score":0.10677832365036011}],"concepts":[{"id":"https://openalex.org/C2779343474","wikidata":"https://www.wikidata.org/wiki/Q3109175","display_name":"Context (archaeology)","level":2,"score":0.6673348546028137},{"id":"https://openalex.org/C81917197","wikidata":"https://www.wikidata.org/wiki/Q628760","display_name":"Selection (genetic algorithm)","level":2,"score":0.6197221279144287},{"id":"https://openalex.org/C73602740","wikidata":"https://www.wikidata.org/wiki/Q7795822","display_name":"Thompson sampling","level":3,"score":0.6132960319519043},{"id":"https://openalex.org/C140779682","wikidata":"https://www.wikidata.org/wiki/Q210868","display_name":"Sampling (signal processing)","level":3,"score":0.5995393991470337},{"id":"https://openalex.org/C181789720","wikidata":"https://www.wikidata.org/wiki/Q4812191","display_name":"Asymptotically optimal algorithm","level":2,"score":0.5929062366485596},{"id":"https://openalex.org/C189430467","wikidata":"https://www.wikidata.org/wiki/Q7293293","display_name":"Ranking (information retrieval)","level":2,"score":0.5743672251701355},{"id":"https://openalex.org/C45357846","wikidata":"https://www.wikidata.org/wiki/Q2001982","display_name":"Notation","level":2,"score":0.5469163656234741},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5088582038879395},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.42378589510917664},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3747093677520752},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.3706960082054138},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.34631651639938354},{"id":"https://openalex.org/C107673813","wikidata":"https://www.wikidata.org/wiki/Q812534","display_name":"Bayesian probability","level":2,"score":0.31579452753067017},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.30817073583602905},{"id":"https://openalex.org/C94375191","wikidata":"https://www.wikidata.org/wiki/Q11205","display_name":"Arithmetic","level":1,"score":0.10677832365036011},{"id":"https://openalex.org/C151730666","wikidata":"https://www.wikidata.org/wiki/Q7205","display_name":"Paleontology","level":1,"score":0.0},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.0},{"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/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tase.2024.3391020","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tase.2024.3391020","pdf_url":null,"source":{"id":"https://openalex.org/S34881539","display_name":"IEEE Transactions on Automation Science and Engineering","issn_l":"1545-5955","issn":["1545-5955","1558-3783"],"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 Automation Science and Engineering","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.800000011920929,"id":"https://metadata.un.org/sdg/16","display_name":"Peace, Justice and strong institutions"}],"awards":[{"id":"https://openalex.org/G4237507856","display_name":null,"funder_award_id":"72022001","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G5000353314","display_name":null,"funder_award_id":"72250065","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G5383787908","display_name":null,"funder_award_id":"U2268209","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G8221598557","display_name":null,"funder_award_id":"72325007","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":57,"referenced_works":["https://openalex.org/W1128523153","https://openalex.org/W1536615069","https://openalex.org/W1598846723","https://openalex.org/W1778518767","https://openalex.org/W2037728958","https://openalex.org/W2046282120","https://openalex.org/W2047808226","https://openalex.org/W2054222839","https://openalex.org/W2078594829","https://openalex.org/W2098432798","https://openalex.org/W2112420033","https://openalex.org/W2144304907","https://openalex.org/W2161551046","https://openalex.org/W2280174025","https://openalex.org/W2312449412","https://openalex.org/W2320597598","https://openalex.org/W2375650553","https://openalex.org/W2607129756","https://openalex.org/W2747244135","https://openalex.org/W2782884958","https://openalex.org/W2792277770","https://openalex.org/W2793133812","https://openalex.org/W2912800932","https://openalex.org/W2922183461","https://openalex.org/W2963653944","https://openalex.org/W2964001381","https://openalex.org/W2964059559","https://openalex.org/W2964339065","https://openalex.org/W2974103621","https://openalex.org/W2974446730","https://openalex.org/W3013160592","https://openalex.org/W3106107128","https://openalex.org/W3121665968","https://openalex.org/W3129972323","https://openalex.org/W3138938129","https://openalex.org/W3140281130","https://openalex.org/W3151384567","https://openalex.org/W3171580098","https://openalex.org/W3202273159","https://openalex.org/W4200286937","https://openalex.org/W4210869902","https://openalex.org/W4212920552","https://openalex.org/W4237029372","https://openalex.org/W4251948628","https://openalex.org/W4252163465","https://openalex.org/W4295662476","https://openalex.org/W4296995036","https://openalex.org/W4313565111","https://openalex.org/W4386031878","https://openalex.org/W4386069692","https://openalex.org/W4388827248","https://openalex.org/W6600390421","https://openalex.org/W6678092311","https://openalex.org/W6681605418","https://openalex.org/W6684588553","https://openalex.org/W6734126808","https://openalex.org/W6759044151"],"related_works":["https://openalex.org/W2536838197","https://openalex.org/W1967128863","https://openalex.org/W2148298232","https://openalex.org/W4375957703","https://openalex.org/W2767931851","https://openalex.org/W4299364030","https://openalex.org/W4383047238","https://openalex.org/W3174325474","https://openalex.org/W2964045314","https://openalex.org/W2610898629"],"abstract_inverted_index":{"We":[0,148,169],"consider":[1,149],"a":[2,26,37,44,129,150,171,195,201],"simulation":[3],"optimization":[4],"problem":[5,41,199],"for":[6,22,110,221],"context-dependent":[7,119,151,217],"decision-making,":[8],"which":[9,156],"aims":[10],"to":[11,48,66,86,96,124,160,167,175],"determine":[12],"the":[13,31,51,68,74,104,108,144,180,208,214,222],"top-":[14,112,181,223],"<inline-formula":[15,113,182,224],"xmlns:mml=\"http://www.w3.org/1998/Math/MathML\"":[16,114,122,183,225],"xmlns:xlink=\"http://www.w3.org/1999/xlink\">":[17,115,184,226],"<tex-math":[18,116,185,227],"notation=\"LaTeX\">$m$</tex-math>":[19,117,186,228],"</inline-formula>":[20,118,187,229],"designs":[21,188],"all":[23,190],"contexts.":[24,191],"Under":[25],"Bayesian":[27],"framework,":[28],"we":[29],"formulate":[30],"optimal":[32,61,69,158],"dynamic":[33,39,172],"sampling":[34,46,62,82,92,173,210],"decision":[35],"as":[36],"stochastic":[38],"programming":[40],"and":[42,89,137,153,178,200,219],"develop":[43,170],"sequential":[45],"policy":[47,83],"efficiently":[49,176],"learn":[50,177],"performance":[52,127],"of":[53,73,77,128,216],"each":[54,57],"design":[55,131],"under":[56],"context.":[58],"The":[59,80],"asymptotically":[60,98],"ratios":[63,93],"are":[64,94],"derived":[65],"attain":[67],"large":[70],"deviations":[71],"rate":[72],"worst-case":[75],"probability":[76],"false":[78],"selection.":[79],"proposed":[81,105,209],"is":[84,140],"proved":[85],"be":[87,97],"consistent,":[88],"its":[90],"asymptotic":[91],"shown":[95],"optimal.":[99],"Numerical":[100,192],"experiments":[101],"demonstrate":[102,206],"that":[103,207],"method":[106],"improves":[107,213],"efficiency":[109,215],"selecting":[111],"designs.":[120,230],"<italic":[121],"xmlns:xlink=\"http://www.w3.org/1999/xlink\">Note":[123],"Practitioners</i>":[125],"\u2014The":[126],"given":[130],"may":[132],"vary":[133],"across":[134],"different":[135],"contexts,":[136],"better":[138],"decision-making":[139],"possible":[141],"by":[142],"refining":[143],"available":[145],"contextual":[146,163],"information.":[147],"ranking":[152,218],"selection":[154,159,220],"problem,":[155,205],"allows":[157],"depend":[161],"on":[162],"information":[164],"obtained":[165],"prior":[166],"decision-making.":[168],"scheme":[174,211],"select":[179],"in":[189],"experiments,":[193],"including":[194],"honeypot":[196],"deception":[197],"game":[198],"medical":[202],"resource":[203],"allocation":[204],"significantly":[212]},"counts_by_year":[{"year":2025,"cited_by_count":4},{"year":2024,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2024-04-30T00:00:00"}