{"id":"https://openalex.org/W7163082178","doi":"https://doi.org/10.48550/arxiv.2605.30976","title":"Batched Stochastic Linear Bandits with 1-Bit Communication Constraints","display_name":"Batched Stochastic Linear Bandits with 1-Bit Communication Constraints","publication_year":2026,"publication_date":"2026-05-29","ids":{"openalex":"https://openalex.org/W7163082178","doi":"https://doi.org/10.48550/arxiv.2605.30976"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2605.30976","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2605.30976","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Preprint"},"type":"preprint","indexed_in":["datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://doi.org/10.48550/arxiv.2605.30976","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5137589035","display_name":"Ivan Lau","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Lau, Ivan","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5119832016","display_name":"Daniel McMorrow","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"McMorrow, Daniel","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5061414344","display_name":"Kevin Jamieson","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Jamieson, Kevin","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5137544008","display_name":"Jonathan Scarlett","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Scarlett, Jonathan","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":0,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12101","display_name":"Advanced Bandit Algorithms Research","score":0.9743000268936157,"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":0.9743000268936157,"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/T11612","display_name":"Stochastic Gradient Optimization Techniques","score":0.00930000003427267,"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/T13553","display_name":"Age of Information Optimization","score":0.00430000014603138,"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":0.729200005531311},{"id":"https://openalex.org/keywords/minimax","display_name":"Minimax","score":0.7138000130653381},{"id":"https://openalex.org/keywords/logarithm","display_name":"Logarithm","score":0.6891000270843506},{"id":"https://openalex.org/keywords/upper-and-lower-bounds","display_name":"Upper and lower bounds","score":0.6735000014305115},{"id":"https://openalex.org/keywords/quantization","display_name":"Quantization (signal processing)","score":0.6431999802589417},{"id":"https://openalex.org/keywords/scaling","display_name":"Scaling","score":0.5184999704360962},{"id":"https://openalex.org/keywords/matching","display_name":"Matching (statistics)","score":0.4514999985694885}],"concepts":[{"id":"https://openalex.org/C50817715","wikidata":"https://www.wikidata.org/wiki/Q79895177","display_name":"Regret","level":2,"score":0.729200005531311},{"id":"https://openalex.org/C149728462","wikidata":"https://www.wikidata.org/wiki/Q751319","display_name":"Minimax","level":2,"score":0.7138000130653381},{"id":"https://openalex.org/C39927690","wikidata":"https://www.wikidata.org/wiki/Q11197","display_name":"Logarithm","level":2,"score":0.6891000270843506},{"id":"https://openalex.org/C77553402","wikidata":"https://www.wikidata.org/wiki/Q13222579","display_name":"Upper and lower bounds","level":2,"score":0.6735000014305115},{"id":"https://openalex.org/C28855332","wikidata":"https://www.wikidata.org/wiki/Q198099","display_name":"Quantization (signal processing)","level":2,"score":0.6431999802589417},{"id":"https://openalex.org/C99844830","wikidata":"https://www.wikidata.org/wiki/Q102441924","display_name":"Scaling","level":2,"score":0.5184999704360962},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.4828000068664551},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.482699990272522},{"id":"https://openalex.org/C165064840","wikidata":"https://www.wikidata.org/wiki/Q1321061","display_name":"Matching (statistics)","level":2,"score":0.4514999985694885},{"id":"https://openalex.org/C28761237","wikidata":"https://www.wikidata.org/wiki/Q7805321","display_name":"Time horizon","level":2,"score":0.4404999911785126},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.4278999865055084},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.40610000491142273},{"id":"https://openalex.org/C196921405","wikidata":"https://www.wikidata.org/wiki/Q786431","display_name":"Online algorithm","level":2,"score":0.321399986743927},{"id":"https://openalex.org/C116834253","wikidata":"https://www.wikidata.org/wiki/Q2039217","display_name":"Identification (biology)","level":2,"score":0.3068000078201294},{"id":"https://openalex.org/C6802819","wikidata":"https://www.wikidata.org/wiki/Q1072174","display_name":"Linear system","level":2,"score":0.26269999146461487},{"id":"https://openalex.org/C122123141","wikidata":"https://www.wikidata.org/wiki/Q176623","display_name":"Random variable","level":2,"score":0.26179999113082886},{"id":"https://openalex.org/C159176650","wikidata":"https://www.wikidata.org/wiki/Q43261","display_name":"Horizon","level":2,"score":0.2572999894618988}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2605.30976","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2605.30976","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"Preprint"}],"best_oa_location":{"id":"doi:10.48550/arxiv.2605.30976","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2605.30976","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Preprint"},"sustainable_development_goals":[{"score":0.40143871307373047,"display_name":"Decent work and economic growth","id":"https://metadata.un.org/sdg/8"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"We":[0,106,152],"study":[1],"stochastic":[2],"linear":[3,243],"bandits":[4,244],"under":[5],"a":[6,49,88,108,139,190,227],"natural":[7],"combination":[8],"of":[9,21,52,130,143,215,230,241],"batching":[10],"and":[11,25,46,161,186,193],"communication":[12,124],"constraints:":[13],"the":[14,29,42,55,60,63,67,122,128,173,187,238],"time":[15],"horizon":[16],"is":[17,118,209],"partitioned":[18],"into":[19],"batches":[20],"equal":[22],"size":[23],"$B$,":[24],"during":[26],"each":[27,58],"batch":[28,233,251],"learner":[30,61],"sends":[31],"$B$":[32,44],"requested":[33],"arm":[34],"pulls":[35],"to":[36,54,121,177,196,235],"an":[37],"agent,":[38],"who":[39],"then":[40],"observes":[41],"corresponding":[43],"rewards":[45,83],"responds":[47],"with":[48,133],"single":[50,228],"bit":[51,103,229],"feedback":[53,231],"learner.":[56],"For":[57],"batch,":[59],"specifies":[62],"1-bit":[64,123,162],"quantization":[65,99],"rule":[66],"agent":[68],"uses,":[69],"which":[70,208],"may":[71],"depend":[72],"on":[73,80,158],"all":[74],"previously":[75],"received":[76],"bits":[77],"but":[78],"not":[79],"any":[81],"past":[82],"directly.":[84],"This":[85],"setting":[86],"addresses":[87],"significant":[89],"yet":[90],"unexplored":[91],"``middle":[92],"ground''":[93],"between":[94],"previous":[95],"models":[96],"having":[97],"per-round":[98],"only":[100],"or":[101],"total":[102],"budgets":[104],"only.":[105],"establish":[107],"minimax":[109,239],"lower":[110,141,174],"bound":[111,142,175],"showing":[112],"that":[113,226],"$\u03a9(B\\min\\{d,\\log\\lvert":[114],"\\mathcal{A}":[115,145,150,182,199,205,217],"\\rvert\\})$":[116],"regret":[117,240],"unavoidable":[119],"due":[120],"bottleneck,":[125],"even":[126,249],"in":[127,211,245],"absence":[129],"noise.":[131],"Combined":[132],"standard":[134],"statistical":[135],"limits,":[136],"this":[137],"yields":[138],"general":[140],"$\\widetilde\u03a9(B\\min\\{d,\\log\\lvert":[144],"\\rvert\\}":[146],"+":[147,169,201,203],"\\sqrt{dT":[148],"\\min\\{d,\\log\\lvert":[149],"\\rvert\\}})$.":[151],"develop":[153],"two":[154],"phased-elimination":[155],"algorithms":[156],"based":[157],"$G$-optimal":[159],"designs":[160],"mean":[163],"estimation.":[164],"The":[165],"first":[166],"achieves":[167],"$\\widetilde{O}(dB":[168],"d\\sqrt{T})$":[170],"regret,":[171,207],"matching":[172],"up":[176],"logarithmic":[178],"factors":[179],"when":[180],"$\\lvert":[181],"\\rvert":[183,200],"=":[184],"\\exp(\u03a9(d))$,":[185],"second":[188],"incorporates":[189],"safe-arm":[191],"identification":[192],"warm-start":[194],"procedure":[195],"obtain":[197],"$\\widetilde{O}(B\\log\\lvert":[198],"d^{3/2}\\sqrt{B}":[202],"\\sqrt{dT\\log\\lvert":[204],"\\rvert})$":[206],"near-optimal":[210],"broad":[212,246],"scaling":[213,247],"regimes":[214],"$(\\lvert":[216],"\\rvert,":[218],"B,":[219],"d,":[220],"T)$.":[221],"Together,":[222],"our":[223],"results":[224],"demonstrate":[225],"per":[232],"suffices":[234],"nearly":[236],"match":[237],"unconstrained":[242],"regimes,":[248],"for":[250],"sizes":[252],"as":[253,255],"large":[254],"$\u0398(\\sqrt{T})$.":[256]},"counts_by_year":[],"updated_date":"2026-07-28T07:46:37.118299","created_date":"2026-06-02T00:00:00"}