{"id":"https://openalex.org/W3047522346","doi":"https://doi.org/10.1109/infocom41043.2020.9155466","title":"Optimizing Mixture Importance Sampling Via Online Learning: Algorithms and Applications","display_name":"Optimizing Mixture Importance Sampling Via Online Learning: Algorithms and Applications","publication_year":2020,"publication_date":"2020-07-01","ids":{"openalex":"https://openalex.org/W3047522346","doi":"https://doi.org/10.1109/infocom41043.2020.9155466","mag":"3047522346"},"language":"en","primary_location":{"id":"doi:10.1109/infocom41043.2020.9155466","is_oa":false,"landing_page_url":"https://doi.org/10.1109/infocom41043.2020.9155466","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE INFOCOM 2020 - IEEE Conference on Computer Communications","raw_type":"proceedings-article"},"type":"conference-paper","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/A5025275705","display_name":"Tingwei Liu","orcid":null},"institutions":[{"id":"https://openalex.org/I177725633","display_name":"Chinese University of Hong Kong","ror":"https://ror.org/00t33hh48","country_code":"HK","type":"education","lineage":["https://openalex.org/I177725633"]}],"countries":["HK"],"is_corresponding":false,"raw_author_name":"Tingwei Liu","raw_affiliation_strings":["Department of Computer Science & Engineering, The Chinese University of Hong Kong, HKSAR"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Computer Science & Engineering, The Chinese University of Hong Kong, HKSAR","institution_ids":["https://openalex.org/I177725633"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5064190343","display_name":"Hong Xie","orcid":"https://orcid.org/0000-0001-7935-7210"},"institutions":[{"id":"https://openalex.org/I158842170","display_name":"Chongqing University","ror":"https://ror.org/023rhb549","country_code":"CN","type":"education","lineage":["https://openalex.org/I158842170"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Hong Xie","raw_affiliation_strings":["College of Computer Science, Chongqing University, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"College of Computer Science, Chongqing University, China","institution_ids":["https://openalex.org/I158842170"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5068489266","display_name":"John C. S. Lui","orcid":"https://orcid.org/0000-0001-7466-0384"},"institutions":[{"id":"https://openalex.org/I177725633","display_name":"Chinese University of Hong Kong","ror":"https://ror.org/00t33hh48","country_code":"HK","type":"education","lineage":["https://openalex.org/I177725633"]}],"countries":["HK"],"is_corresponding":false,"raw_author_name":"John C.S. Lui","raw_affiliation_strings":["Department of Computer Science & Engineering, The Chinese University of Hong Kong, HKSAR"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Computer Science & Engineering, The Chinese University of Hong Kong, HKSAR","institution_ids":["https://openalex.org/I177725633"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.1287201,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"149","last_page":"158"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12101","display_name":"Advanced Bandit Algorithms Research","score":0.9993000030517578,"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/T12101","display_name":"Advanced Bandit Algorithms Research","score":0.9993000030517578,"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/T13553","display_name":"Age of Information Optimization","score":0.9987000226974487,"subfield":{"id":"https://openalex.org/subfields/1705","display_name":"Computer Networks and Communications"},"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/T12288","display_name":"Optimization and Search Problems","score":0.9939000010490417,"subfield":{"id":"https://openalex.org/subfields/1705","display_name":"Computer Networks and Communications"},"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/regret","display_name":"Regret","score":0.8015259504318237},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6996214985847473},{"id":"https://openalex.org/keywords/event","display_name":"Event (particle physics)","score":0.666736900806427},{"id":"https://openalex.org/keywords/sampling","display_name":"Sampling (signal processing)","score":0.62771075963974},{"id":"https://openalex.org/keywords/thompson-sampling","display_name":"Thompson sampling","score":0.5941238403320312},{"id":"https://openalex.org/keywords/importance-sampling","display_name":"Importance sampling","score":0.49294281005859375},{"id":"https://openalex.org/keywords/rare-events","display_name":"Rare events","score":0.472958505153656},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.43890637159347534},{"id":"https://openalex.org/keywords/mathematical-optimization","display_name":"Mathematical optimization","score":0.43004825711250305},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.35551154613494873},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.34313148260116577},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.18240660429000854},{"id":"https://openalex.org/keywords/monte-carlo-method","display_name":"Monte Carlo method","score":0.13059577345848083},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.11727935075759888}],"concepts":[{"id":"https://openalex.org/C50817715","wikidata":"https://www.wikidata.org/wiki/Q79895177","display_name":"Regret","level":2,"score":0.8015259504318237},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6996214985847473},{"id":"https://openalex.org/C2779662365","wikidata":"https://www.wikidata.org/wiki/Q5416694","display_name":"Event (particle physics)","level":2,"score":0.666736900806427},{"id":"https://openalex.org/C140779682","wikidata":"https://www.wikidata.org/wiki/Q210868","display_name":"Sampling (signal processing)","level":3,"score":0.62771075963974},{"id":"https://openalex.org/C73602740","wikidata":"https://www.wikidata.org/wiki/Q7795822","display_name":"Thompson sampling","level":3,"score":0.5941238403320312},{"id":"https://openalex.org/C52740198","wikidata":"https://www.wikidata.org/wiki/Q1539564","display_name":"Importance sampling","level":3,"score":0.49294281005859375},{"id":"https://openalex.org/C2777317252","wikidata":"https://www.wikidata.org/wiki/Q18393516","display_name":"Rare events","level":2,"score":0.472958505153656},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.43890637159347534},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.43004825711250305},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.35551154613494873},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.34313148260116577},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.18240660429000854},{"id":"https://openalex.org/C19499675","wikidata":"https://www.wikidata.org/wiki/Q232207","display_name":"Monte Carlo method","level":2,"score":0.13059577345848083},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.11727935075759888},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","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/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"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}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/infocom41043.2020.9155466","is_oa":false,"landing_page_url":"https://doi.org/10.1109/infocom41043.2020.9155466","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE INFOCOM 2020 - IEEE Conference on Computer Communications","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":31,"referenced_works":["https://openalex.org/W34142743","https://openalex.org/W1621653743","https://openalex.org/W1665662210","https://openalex.org/W1706962981","https://openalex.org/W2014426364","https://openalex.org/W2029241234","https://openalex.org/W2064907085","https://openalex.org/W2077723394","https://openalex.org/W2087018957","https://openalex.org/W2098152875","https://openalex.org/W2120353978","https://openalex.org/W2126822952","https://openalex.org/W2136325069","https://openalex.org/W2136885855","https://openalex.org/W2137300478","https://openalex.org/W2468229791","https://openalex.org/W2530513829","https://openalex.org/W2746804892","https://openalex.org/W2963100806","https://openalex.org/W2963557086","https://openalex.org/W2963915403","https://openalex.org/W3042220830","https://openalex.org/W4231714045","https://openalex.org/W4235045732","https://openalex.org/W4292022450","https://openalex.org/W4297728837","https://openalex.org/W6637612152","https://openalex.org/W6679677315","https://openalex.org/W6719981591","https://openalex.org/W6743400193","https://openalex.org/W6813567453"],"related_works":["https://openalex.org/W3108185025","https://openalex.org/W1850547517","https://openalex.org/W2964125852","https://openalex.org/W3176022311","https://openalex.org/W3048056964","https://openalex.org/W4287690869","https://openalex.org/W3046298489","https://openalex.org/W3015709540","https://openalex.org/W4287816990","https://openalex.org/W2160389399"],"abstract_inverted_index":{"Importance":[0],"sampling":[1,91],"(IS)":[2],"is":[3,12,109],"widely":[4],"used":[5],"in":[6],"rare":[7,18,24,52,63,84],"event":[8,25,64],"simulation,":[9],"but":[10],"it":[11,115,202],"costly":[13],"to":[14,30,45,60,95,112,117,134],"deal":[15,46],"with":[16,47,65,165,176,222],"many":[17,48],"events":[19],"simultaneously.":[20],"For":[21],"example,":[22],"a":[23,36,125,166,177,196],"can":[26,203],"be":[27],"the":[28,32,88,97,104,119,136,141,160,173,186,205,223],"failure":[29],"provide":[31],"quality-of-service":[33],"guarantee":[34],"for":[35,82],"critical":[37,49],"network":[38,41,198],"flow.":[39],"Since":[40],"providers":[42,58],"often":[43],"need":[44],"flows":[50],"(i.e.,":[51,208],"events)":[53],"simultaneously,":[54],"if":[55],"using":[56],"IS,":[57],"have":[59],"simulate":[61],"each":[62],"its":[66],"customized":[67],"importance":[68,80,90],"distribution":[69,81],"individually.":[70],"To":[71],"reduce":[72,204],"such":[73],"cost,":[74],"we":[75],"propose":[76],"an":[77],"efficient":[78],"mixture":[79,89,108,143,225],"multiple":[83],"events,":[85],"and":[86,139,199,213],"formulate":[87,124],"optimization":[92],"problem":[93],"(MISOP)":[94],"select":[96],"optimal":[98,120,142],"mixture.":[99,121],"We":[100,122,149,191],"first":[101],"show":[102,200],"that":[103,201],"\"search":[105,137],"direction\"":[106],"of":[107,147,162,168,179,188,210],"computationally":[110],"expensive":[111],"evaluate,":[113],"making":[114],"challenging":[116],"locate":[118],"then":[123],"\"":[126,130],"zero":[127],"learning":[128,132,155],"cost":[129,175,206],"online":[131,154],"framework":[133],"estimate":[135],"direction\",":[138],"learn":[140],"from":[144],"simulation":[145,174,189,214],"samples":[146],"events.":[148],"develop":[150],"two":[151],"multi-armed":[152],"bandit":[153],"algorithms":[156],"to:":[157],"(1)":[158],"Minimize":[159,172],"sum":[161,209],"estimation":[163,211],"variances":[164,212],"regret":[167,178],"(ln":[169],"T)2/T;":[170],"(2)":[171],"\u221aln":[180],"T/T":[181],",":[182],"where":[183],"T":[184],"denotes":[185],"number":[187],"samples.":[190],"demonstrate":[192],"our":[193],"method":[194],"on":[195],"realistic":[197],"measures":[207],"cost)":[215],"by":[216],"as":[217,219],"high":[218],"61.6%":[220],"compared":[221],"uniform":[224],"IS.":[226]},"counts_by_year":[],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-10-10T00:00:00"}
