{"id":"https://openalex.org/W3176606742","doi":"https://doi.org/10.1145/3466772.3467031","title":"Learning-NUM","display_name":"Learning-NUM","publication_year":2021,"publication_date":"2021-06-29","ids":{"openalex":"https://openalex.org/W3176606742","doi":"https://doi.org/10.1145/3466772.3467031","mag":"3176606742"},"language":"en","primary_location":{"id":"doi:10.1145/3466772.3467031","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3466772.3467031","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3466772.3467031","source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the Twenty-second International Symposium on Theory, Algorithmic Foundations, and Protocol Design for Mobile Networks and Mobile Computing","raw_type":"proceedings-article"},"type":"conference-paper","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://dl.acm.org/doi/pdf/10.1145/3466772.3467031","any_repository_has_fulltext":null},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5049286032","display_name":"Xinzhe Fu","orcid":"https://orcid.org/0000-0002-4425-3881"},"institutions":[{"id":"https://openalex.org/I63966007","display_name":"Massachusetts Institute of Technology","ror":"https://ror.org/042nb2s44","country_code":"US","type":"education","lineage":["https://openalex.org/I63966007"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Xinzhe Fu","raw_affiliation_strings":["LIDS, Massachusetts Institute of Technology, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"LIDS, Massachusetts Institute of Technology, USA","institution_ids":["https://openalex.org/I63966007"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5036587377","display_name":"Eytan Modiano","orcid":null},"institutions":[{"id":"https://openalex.org/I63966007","display_name":"Massachusetts Institute of Technology","ror":"https://ror.org/042nb2s44","country_code":"US","type":"education","lineage":["https://openalex.org/I63966007"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Eytan Modiano","raw_affiliation_strings":["LIDS, Massachusetts Institute of Technology, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"LIDS, Massachusetts Institute of Technology, USA","institution_ids":["https://openalex.org/I63966007"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I63966007"],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":true,"cited_by_count":12,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"21","last_page":"30"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11409","display_name":"Advanced Wireless Network Optimization","score":0.9998000264167786,"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/T11409","display_name":"Advanced Wireless Network Optimization","score":0.9998000264167786,"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/T13553","display_name":"Age of Information Optimization","score":0.9993000030517578,"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/T10138","display_name":"Network Traffic and Congestion Control","score":0.9976000189781189,"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":0.7746133804321289},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7618426084518433},{"id":"https://openalex.org/keywords/utility-maximization-problem","display_name":"Utility maximization problem","score":0.7174035906791687},{"id":"https://openalex.org/keywords/mathematical-optimization","display_name":"Mathematical optimization","score":0.6208580136299133},{"id":"https://openalex.org/keywords/queueing-theory","display_name":"Queueing theory","score":0.5847769975662231},{"id":"https://openalex.org/keywords/scheduling","display_name":"Scheduling (production processes)","score":0.5346744656562805},{"id":"https://openalex.org/keywords/utility-maximization","display_name":"Utility maximization","score":0.5153471827507019},{"id":"https://openalex.org/keywords/queuing-delay","display_name":"Queuing delay","score":0.46836745738983154},{"id":"https://openalex.org/keywords/dynamic-programming","display_name":"Dynamic programming","score":0.44250544905662537},{"id":"https://openalex.org/keywords/reinforcement-learning","display_name":"Reinforcement learning","score":0.4132033586502075},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.1325315535068512},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.12928500771522522},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.12315163016319275},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.10032644867897034},{"id":"https://openalex.org/keywords/computer-network","display_name":"Computer network","score":0.09735250473022461}],"concepts":[{"id":"https://openalex.org/C50817715","wikidata":"https://www.wikidata.org/wiki/Q79895177","display_name":"Regret","level":2,"score":0.7746133804321289},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7618426084518433},{"id":"https://openalex.org/C2779044140","wikidata":"https://www.wikidata.org/wiki/Q3274096","display_name":"Utility maximization problem","level":3,"score":0.7174035906791687},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.6208580136299133},{"id":"https://openalex.org/C22684755","wikidata":"https://www.wikidata.org/wiki/Q847526","display_name":"Queueing theory","level":2,"score":0.5847769975662231},{"id":"https://openalex.org/C206729178","wikidata":"https://www.wikidata.org/wiki/Q2271896","display_name":"Scheduling (production processes)","level":2,"score":0.5346744656562805},{"id":"https://openalex.org/C2985793214","wikidata":"https://www.wikidata.org/wiki/Q3274096","display_name":"Utility maximization","level":2,"score":0.5153471827507019},{"id":"https://openalex.org/C196095461","wikidata":"https://www.wikidata.org/wiki/Q576842","display_name":"Queuing delay","level":3,"score":0.46836745738983154},{"id":"https://openalex.org/C37404715","wikidata":"https://www.wikidata.org/wiki/Q380679","display_name":"Dynamic programming","level":2,"score":0.44250544905662537},{"id":"https://openalex.org/C97541855","wikidata":"https://www.wikidata.org/wiki/Q830687","display_name":"Reinforcement learning","level":2,"score":0.4132033586502075},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.1325315535068512},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.12928500771522522},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.12315163016319275},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.10032644867897034},{"id":"https://openalex.org/C31258907","wikidata":"https://www.wikidata.org/wiki/Q1301371","display_name":"Computer network","level":1,"score":0.09735250473022461},{"id":"https://openalex.org/C144237770","wikidata":"https://www.wikidata.org/wiki/Q747534","display_name":"Mathematical economics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3466772.3467031","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3466772.3467031","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3466772.3467031","source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the Twenty-second International Symposium on Theory, Algorithmic Foundations, and Protocol Design for Mobile Networks and Mobile Computing","raw_type":"proceedings-article"}],"best_oa_location":{"id":"doi:10.1145/3466772.3467031","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3466772.3467031","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3466772.3467031","source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the Twenty-second International Symposium on Theory, Algorithmic Foundations, and Protocol Design for Mobile Networks and Mobile Computing","raw_type":"proceedings-article"},"sustainable_development_goals":[{"score":0.5099999904632568,"id":"https://metadata.un.org/sdg/8","display_name":"Decent work and economic growth"}],"awards":[{"id":"https://openalex.org/G4949411081","display_name":null,"funder_award_id":"N00014-20-1-2119","funder_id":"https://openalex.org/F4320337345","funder_display_name":"Office of Naval Research"},{"id":"https://openalex.org/G8409476322","display_name":"NeTS: Small:  A Migration Approach to Optimal Control of Wireless Networks","funder_award_id":"1524317","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"},{"id":"https://openalex.org/G8445870396","display_name":null,"funder_award_id":"CNS-1524317","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"},{"id":"https://openalex.org/G8876996369","display_name":null,"funder_award_id":"N00014","funder_id":"https://openalex.org/F4320337345","funder_display_name":"Office of Naval Research"}],"funders":[{"id":"https://openalex.org/F4320306076","display_name":"National Science Foundation","ror":"https://ror.org/021nxhr62"},{"id":"https://openalex.org/F4320337345","display_name":"Office of Naval Research","ror":"https://ror.org/00rk2pe57"}],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W3176606742.pdf","grobid_xml":"https://content.openalex.org/works/W3176606742.grobid-xml"},"referenced_works_count":36,"referenced_works":["https://openalex.org/W1574233349","https://openalex.org/W1996704710","https://openalex.org/W2004001705","https://openalex.org/W2006689319","https://openalex.org/W2022575296","https://openalex.org/W2037710455","https://openalex.org/W2038888321","https://openalex.org/W2057415916","https://openalex.org/W2077723394","https://openalex.org/W2100050269","https://openalex.org/W2104842473","https://openalex.org/W2105177639","https://openalex.org/W2120344179","https://openalex.org/W2137677949","https://openalex.org/W2159715570","https://openalex.org/W2160262323","https://openalex.org/W2161615677","https://openalex.org/W2162388481","https://openalex.org/W2165768656","https://openalex.org/W2556949899","https://openalex.org/W2563280975","https://openalex.org/W2565612488","https://openalex.org/W2717920768","https://openalex.org/W2739805727","https://openalex.org/W2749843017","https://openalex.org/W2759085228","https://openalex.org/W2777290315","https://openalex.org/W2953015416","https://openalex.org/W2962725887","https://openalex.org/W2963062786","https://openalex.org/W2963211719","https://openalex.org/W4231523909","https://openalex.org/W6682189477","https://openalex.org/W6683841709","https://openalex.org/W6730110147","https://openalex.org/W6743491589"],"related_works":["https://openalex.org/W2951390543","https://openalex.org/W3121912968","https://openalex.org/W2949260239","https://openalex.org/W2949594337","https://openalex.org/W3123067344","https://openalex.org/W4299412355","https://openalex.org/W2953072363","https://openalex.org/W3125423763","https://openalex.org/W2950840434","https://openalex.org/W2729827172"],"abstract_inverted_index":{"Network":[0],"Utility":[1],"Maximization":[2],"(NUM)":[3],"studies":[4],"the":[5,18,38,46,51,59,65,70,86,101,128,132,141,144,150,156,164,172,183,193,198,212,215,220,233,237,260,266],"problems":[6],"of":[7,50,123,131,143,174,185,236,269],"allocating":[8],"traffic":[9,52,61],"rates":[10,53],"to":[11,16,23,64,79,99,113,166,204,231,243,264],"network":[12,24,94],"users":[13],"in":[14,127,200,228],"order":[15],"maximize":[17,100],"users'":[19,39],"total":[20,102,152],"utility":[21,40,47,71,87,103,115,153,217],"subject":[22],"resource":[25],"constraints.":[26],"In":[27,111],"this":[28],"paper,":[29],"we":[30,177,196,240],"propose":[31],"a":[32,81,106,120,167,201,206],"new":[33],"NUM":[34],"framework,":[35,239],"Learning-NUM,":[36],"where":[37],"functions":[41,88,116],"are":[42],"unknown":[43,114],"apriori":[44],"and":[45,89,93,117,138,188,224,252],"function":[48],"values":[49],"can":[54],"be":[55,136],"observed":[56],"only":[57],"after":[58],"corresponding":[60],"is":[62,78,160,227],"delivered":[63],"destination,":[66],"which":[67,134],"means":[68],"that":[69,83,149,208],"feedback":[72,175,194],"experiences":[73],"queueing":[74,129],"delay.":[75],"The":[76],"goal":[77],"design":[80,178],"policy":[82,159,207,223,226],"gradually":[84],"learns":[85],"makes":[90],"rate":[91],"allocation":[92],"scheduling/routing":[95],"decisions":[96,142],"so":[97],"as":[98],"obtained":[104,154,218],"over":[105],"finite":[107],"time":[108],"horizon":[109],"T.":[110],"addition":[112],"stochastic":[118],"constraints,":[119],"central":[121],"challenge":[122],"our":[124,225,270],"problem":[125],"lies":[126],"delay":[130],"observations,":[133],"may":[135],"unbounded":[137],"depends":[139],"on":[140,182,259],"policy.":[145,271],"We":[146,255],"first":[147],"show":[148],"expected":[151,216],"by":[155,163,219],"best":[157,221],"dynamic":[158,222],"upper":[161],"bounded":[162],"solution":[165],"static":[168],"optimization":[169],"problem.":[170],"Without":[171],"presence":[173],"delay,":[176,195],"an":[179],"algorithm":[180,199],"based":[181],"ideas":[184],"gradient":[186],"estimation":[187],"Max-Weight":[189],"scheduling.":[190],"To":[191],"handle":[192],"embed":[197],"parallel-instance":[202],"paradigm":[203],"form":[205],"achieves":[209],"\u00d5(T3/4)-regret,":[210],"i.e.,":[211],"difference":[213],"between":[214],"\u00d5(T3/4).":[229],"Finally,":[230],"demonstrate":[232],"practical":[234],"applicability":[235],"Learning-NUM":[238],"apply":[241],"it":[242],"three":[244],"application":[245,263],"scenarios":[246],"including":[247],"database":[248],"query,":[249],"job":[250,261],"scheduling":[251,262],"video":[253],"streaming.":[254],"further":[256],"conduct":[257],"simulations":[258],"evaluate":[265],"empirical":[267],"performance":[268]},"counts_by_year":[{"year":2025,"cited_by_count":3},{"year":2024,"cited_by_count":3},{"year":2023,"cited_by_count":2},{"year":2022,"cited_by_count":3},{"year":2021,"cited_by_count":1}],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2021-07-05T00:00:00"}