{"id":"https://openalex.org/W7125914216","doi":"https://doi.org/10.48550/arxiv.2601.18950","title":"Collaborative Compressors in Distributed Mean Estimation with Limited Communication Budget","display_name":"Collaborative Compressors in Distributed Mean Estimation with Limited Communication Budget","publication_year":2026,"publication_date":"2026-01-26","ids":{"openalex":"https://openalex.org/W7125914216","doi":"https://doi.org/10.48550/arxiv.2601.18950"},"language":null,"primary_location":{"id":"pmh:doi:10.48550/arxiv.2601.18950","is_oa":true,"landing_page_url":null,"pdf_url":null,"source":{"id":"https://openalex.org/S4406922384","display_name":"Open MIND","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Article"},"type":"article","indexed_in":["datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":null,"any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5109104268","display_name":"Harsh Vardhan","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Vardhan, Harsh","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":null,"display_name":"Mazumdar, Arya","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Mazumdar, Arya","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":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.09774528,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"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/T11612","display_name":"Stochastic Gradient Optimization Techniques","score":0.8277000188827515,"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"}},"topics":[{"id":"https://openalex.org/T11612","display_name":"Stochastic Gradient Optimization Techniques","score":0.8277000188827515,"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/T10764","display_name":"Privacy-Preserving Technologies in Data","score":0.042500000447034836,"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/T12101","display_name":"Advanced Bandit Algorithms Research","score":0.03869999945163727,"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/exploit","display_name":"Exploit","score":0.7222999930381775},{"id":"https://openalex.org/keywords/cosine-similarity","display_name":"Cosine similarity","score":0.5138999819755554},{"id":"https://openalex.org/keywords/data-compression","display_name":"Data compression","score":0.5049999952316284},{"id":"https://openalex.org/keywords/encode","display_name":"ENCODE","score":0.4535999894142151},{"id":"https://openalex.org/keywords/compression","display_name":"Compression (physics)","score":0.4422000050544739},{"id":"https://openalex.org/keywords/simple","display_name":"Simple (philosophy)","score":0.4244000017642975},{"id":"https://openalex.org/keywords/scheme","display_name":"Scheme (mathematics)","score":0.4115999937057495},{"id":"https://openalex.org/keywords/minification","display_name":"Minification","score":0.39750000834465027}],"concepts":[{"id":"https://openalex.org/C165696696","wikidata":"https://www.wikidata.org/wiki/Q11287","display_name":"Exploit","level":2,"score":0.7222999930381775},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7009999752044678},{"id":"https://openalex.org/C2780762811","wikidata":"https://www.wikidata.org/wiki/Q1784941","display_name":"Cosine similarity","level":3,"score":0.5138999819755554},{"id":"https://openalex.org/C78548338","wikidata":"https://www.wikidata.org/wiki/Q2493","display_name":"Data compression","level":2,"score":0.5049999952316284},{"id":"https://openalex.org/C66746571","wikidata":"https://www.wikidata.org/wiki/Q1134833","display_name":"ENCODE","level":3,"score":0.4535999894142151},{"id":"https://openalex.org/C180016635","wikidata":"https://www.wikidata.org/wiki/Q2712821","display_name":"Compression (physics)","level":2,"score":0.4422000050544739},{"id":"https://openalex.org/C2780586882","wikidata":"https://www.wikidata.org/wiki/Q7520643","display_name":"Simple (philosophy)","level":2,"score":0.4244000017642975},{"id":"https://openalex.org/C77618280","wikidata":"https://www.wikidata.org/wiki/Q1155772","display_name":"Scheme (mathematics)","level":2,"score":0.4115999937057495},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.4000000059604645},{"id":"https://openalex.org/C147764199","wikidata":"https://www.wikidata.org/wiki/Q6865248","display_name":"Minification","level":2,"score":0.39750000834465027},{"id":"https://openalex.org/C81081738","wikidata":"https://www.wikidata.org/wiki/Q55542","display_name":"Lossless compression","level":3,"score":0.37770000100135803},{"id":"https://openalex.org/C96250715","wikidata":"https://www.wikidata.org/wiki/Q965330","display_name":"Estimation","level":2,"score":0.3720000088214874},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.3400000035762787},{"id":"https://openalex.org/C103278499","wikidata":"https://www.wikidata.org/wiki/Q254465","display_name":"Similarity (geometry)","level":3,"score":0.33379998803138733},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.32519999146461487},{"id":"https://openalex.org/C198531522","wikidata":"https://www.wikidata.org/wiki/Q485146","display_name":"Sample (material)","level":2,"score":0.3138999938964844},{"id":"https://openalex.org/C179145077","wikidata":"https://www.wikidata.org/wiki/Q5154130","display_name":"Communication complexity","level":2,"score":0.28290000557899475},{"id":"https://openalex.org/C120314980","wikidata":"https://www.wikidata.org/wiki/Q180634","display_name":"Distributed computing","level":1,"score":0.28279998898506165},{"id":"https://openalex.org/C8505890","wikidata":"https://www.wikidata.org/wiki/Q605095","display_name":"Budget constraint","level":2,"score":0.26989999413490295},{"id":"https://openalex.org/C25797200","wikidata":"https://www.wikidata.org/wiki/Q828137","display_name":"Compression ratio","level":3,"score":0.26809999346733093},{"id":"https://openalex.org/C139945424","wikidata":"https://www.wikidata.org/wiki/Q1940696","display_name":"Mean squared error","level":2,"score":0.2630999982357025},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.26190000772476196},{"id":"https://openalex.org/C77553402","wikidata":"https://www.wikidata.org/wiki/Q13222579","display_name":"Upper and lower bounds","level":2,"score":0.2612000107765198},{"id":"https://openalex.org/C2221639","wikidata":"https://www.wikidata.org/wiki/Q2877","display_name":"Discrete cosine transform","level":3,"score":0.25290000438690186}],"mesh":[],"locations_count":2,"locations":[{"id":"pmh:doi:10.48550/arxiv.2601.18950","is_oa":true,"landing_page_url":null,"pdf_url":null,"source":{"id":"https://openalex.org/S4406922384","display_name":"Open MIND","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Article"},{"id":"doi:10.48550/arxiv.2601.18950","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2601.18950","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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"Preprint"}],"best_oa_location":{"id":"pmh:doi:10.48550/arxiv.2601.18950","is_oa":true,"landing_page_url":null,"pdf_url":null,"source":{"id":"https://openalex.org/S4406922384","display_name":"Open MIND","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Distributed":[0],"high":[1],"dimensional":[2],"mean":[3,28],"estimation":[4,175],"is":[5,29,115],"a":[6,22,101,142],"common":[7],"aggregation":[8],"routine":[9],"used":[10],"often":[11,58],"in":[12,86,121,141,157,160],"distributed":[13,143],"optimization":[14],"methods.":[15],"Most":[16],"of":[17,104,107,164,181],"these":[18,45,55,65,96,108],"applications":[19],"call":[20],"for":[21,95],"communication-constrained":[23],"setting":[24],"where":[25],"vectors,":[26],"whose":[27],"to":[30,34,46,60,92,98,117,150],"be":[31,35,93],"estimated,":[32],"have":[33,91],"compressed":[36],"before":[37],"sharing.":[38],"One":[39],"could":[40],"independently":[41],"encode":[42],"and":[43,152,173],"decode":[44],"achieve":[47],"compression,":[48],"but":[49],"that":[50,54,134],"overlooks":[51],"the":[52,89,119,122,137,170,179],"fact":[53],"vectors":[56,140],"are":[57,147],"close":[59],"each":[61],"other.":[62],"To":[63],"exploit":[64,136],"similarities,":[66],"recently":[67],"Suresh":[68],"et":[69,73,77],"al.,":[70,74],"2022,":[71],"Jhunjhunwala":[72],"2021,":[75],"Jiang":[76],"al,":[78],"2023,":[79],"proposed":[80,166],"multiple":[81],"correlation-aware":[82,109],"compression":[83,110,132],"schemes.":[84],"However,":[85],"most":[87],"cases,":[88],"correlations":[90],"known":[94],"schemes":[97,111,133,146,167],"work.":[99],"Moreover,":[100],"theoretical":[102],"analysis":[103,163],"graceful":[105],"degradation":[106],"with":[112,178],"increasing":[113],"dissimilarity":[114],"limited":[116],"only":[118],"$\\ell_2$-error":[120],"literature.":[123],"In":[124],"this":[125],"paper,":[126],"we":[127],"propose":[128],"four":[129],"different":[130],"collaborative":[131],"agnostically":[135],"similarities":[138],"among":[139,183],"setting.":[144],"Our":[145],"all":[148],"simple":[149],"implement":[151],"computationally":[153],"efficient,":[154],"while":[155],"resulting":[156],"big":[158],"savings":[159],"communication.":[161],"The":[162],"our":[165],"show":[168],"how":[169],"$\\ell_2$,":[171],"$\\ell_\\infty$":[172],"cosine":[174],"error":[176],"varies":[177],"degree":[180],"similarity":[182],"vectors.":[184]},"counts_by_year":[],"updated_date":"2026-07-28T07:46:37.118299","created_date":"2026-01-29T00:00:00"}
