{"id":"https://openalex.org/W2885646085","doi":"https://doi.org/10.1109/isit.2018.8437817","title":"Learning Algorithms for Minimizing Queue Length Regret","display_name":"Learning Algorithms for Minimizing Queue Length Regret","publication_year":2018,"publication_date":"2018-06-01","ids":{"openalex":"https://openalex.org/W2885646085","doi":"https://doi.org/10.1109/isit.2018.8437817","mag":"2885646085"},"language":"en","primary_location":{"id":"doi:10.1109/isit.2018.8437817","is_oa":false,"landing_page_url":"https://doi.org/10.1109/isit.2018.8437817","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2018 IEEE International Symposium on Information Theory (ISIT)","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/A5089109536","display_name":"Thomas Stahlbuhk","orcid":"https://orcid.org/0000-0002-2128-5004"},"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":"Thomas Stahlbuhk","raw_affiliation_strings":["Massachusetts Institute of Technology, Cambridge, MA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Massachusetts Institute of Technology, Cambridge, MA","institution_ids":["https://openalex.org/I63966007"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5047576065","display_name":"Brooke Shrader","orcid":null},"institutions":[{"id":"https://openalex.org/I4210122954","display_name":"MIT Lincoln Laboratory","ror":"https://ror.org/022z6jk58","country_code":"US","type":"facility","lineage":["https://openalex.org/I4210122954","https://openalex.org/I63966007"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Brooke Shrader","raw_affiliation_strings":["MIT Lincoln Laboratory, Lexington, MA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"MIT Lincoln Laboratory, Lexington, MA","institution_ids":["https://openalex.org/I4210122954"]}]},{"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":["Massachusetts Institute of Technology, Cambridge, MA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Massachusetts Institute of Technology, Cambridge, MA","institution_ids":["https://openalex.org/I63966007"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":4.329,"has_fulltext":false,"cited_by_count":18,"citation_normalized_percentile":{"value":0.95386247,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":89,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"1001","last_page":"1005"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12101","display_name":"Advanced Bandit Algorithms Research","score":1.0,"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":1.0,"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/T10462","display_name":"Reinforcement Learning in Robotics","score":0.995199978351593,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"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":0.994700014591217,"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":0.8430230021476746},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7259794473648071},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.5413517951965332},{"id":"https://openalex.org/keywords/queue","display_name":"Queue","score":0.536914050579071},{"id":"https://openalex.org/keywords/computer-network","display_name":"Computer network","score":0.1961388885974884},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.11541962623596191}],"concepts":[{"id":"https://openalex.org/C50817715","wikidata":"https://www.wikidata.org/wiki/Q79895177","display_name":"Regret","level":2,"score":0.8430230021476746},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7259794473648071},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.5413517951965332},{"id":"https://openalex.org/C160403385","wikidata":"https://www.wikidata.org/wiki/Q220543","display_name":"Queue","level":2,"score":0.536914050579071},{"id":"https://openalex.org/C31258907","wikidata":"https://www.wikidata.org/wiki/Q1301371","display_name":"Computer network","level":1,"score":0.1961388885974884},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.11541962623596191}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/isit.2018.8437817","is_oa":false,"landing_page_url":"https://doi.org/10.1109/isit.2018.8437817","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2018 IEEE International Symposium on Information Theory (ISIT)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":12,"referenced_works":["https://openalex.org/W2000080679","https://openalex.org/W2009551863","https://openalex.org/W2039522160","https://openalex.org/W2049934117","https://openalex.org/W2168405694","https://openalex.org/W2339643019","https://openalex.org/W2909511175","https://openalex.org/W2950929549","https://openalex.org/W2963814530","https://openalex.org/W4234228486","https://openalex.org/W6660272072","https://openalex.org/W6703562905"],"related_works":["https://openalex.org/W2748952813","https://openalex.org/W4376155396","https://openalex.org/W2971351794","https://openalex.org/W1947085858","https://openalex.org/W2101991911","https://openalex.org/W2174986909","https://openalex.org/W2527791220","https://openalex.org/W2155070487","https://openalex.org/W4311589891","https://openalex.org/W3123835761"],"abstract_inverted_index":{"We":[0,66],"consider":[1],"a":[2,6,24,84,94,100,147],"system":[3,72],"consisting":[4],"of":[5,29,56,70,83,149],"single":[7],"transmitter":[8],"and":[9,19,43,93],"N":[10,31],"channels.":[11],"Packets":[12],"randomly":[13],"arrive":[14],"to":[15,52,73,104,110,119,156],"the":[16,30,54,59,68,71,75,79,89,98,114,121,139],"transmitter's":[17],"queue,":[18],"at":[20],"each":[21],"time":[22,64],"slot":[23],"controller":[25,85,95],"can":[26],"schedule":[27],"one":[28],"channels":[32],"for":[33],"transmission.":[34],"The":[35],"channel's":[36],"rates":[37,92],"are":[38,154],"time-varying":[39],"with":[40],"unknown":[41],"statistics":[42],"must":[44,87],"be":[45,74,109],"learned":[46],"through":[47],"observation.":[48],"Our":[49],"objective":[50],"is":[51],"minimize":[53],"number":[55],"packets":[57],"in":[58],"system's":[60],"queue":[61,81,135],"over":[62],"T":[63],"slots.":[65],"define":[67],"regret":[69],"expected":[76],"difference":[77],"between":[78],"total":[80],"length":[82,136],"that":[86,96,116,130,144,153],"learn":[88],"channels'":[90],"average":[91],"knows":[97],"rates,":[99],"priori.":[101],"One":[102],"approach":[103],"solving":[105],"this":[106],"problem":[107],"would":[108],"apply":[111],"algorithms":[112],"from":[113],"literature":[115],"were":[117],"developed":[118],"solve":[120],"closely-related":[122],"stochastic":[123],"multi-armed":[124],"bandit":[125],"problem.":[126],"However,":[127],"we":[128,142],"show":[129,143],"these":[131],"methods":[132],"have":[133],"\u03a9(log(T))":[134],"regret.":[137,161],"On":[138],"other":[140],"hand,":[141],"there":[145],"exists":[146],"set":[148],"queue-length":[150],"based":[151],"policies":[152],"able":[155],"obtain":[157],"order":[158],"optimal,":[159],"O(1),":[160]},"counts_by_year":[{"year":2025,"cited_by_count":2},{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":1},{"year":2022,"cited_by_count":1},{"year":2021,"cited_by_count":10},{"year":2020,"cited_by_count":2},{"year":2018,"cited_by_count":1}],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-10-10T00:00:00"}
