{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,6,19]],"date-time":"2025-06-19T05:53:35Z","timestamp":1750312415804,"version":"3.37.3"},"reference-count":56,"publisher":"Institute of Electrical and Electronics Engineers (IEEE)","issue":"12","license":[{"start":{"date-parts":[[2021,12,1]],"date-time":"2021-12-01T00:00:00Z","timestamp":1638316800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/ieeexplore.ieee.org\/Xplorehelp\/downloads\/license-information\/IEEE.html"},{"start":{"date-parts":[[2021,12,1]],"date-time":"2021-12-01T00:00:00Z","timestamp":1638316800000},"content-version":"am","delay-in-days":0,"URL":"https:\/\/ieeexplore.ieee.org\/Xplorehelp\/downloads\/license-information\/IEEE.html"},{"start":{"date-parts":[[2021,12,1]],"date-time":"2021-12-01T00:00:00Z","timestamp":1638316800000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2021,12,1]],"date-time":"2021-12-01T00:00:00Z","timestamp":1638316800000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"}],"funder":[{"name":"NSF Center for the Science of Information"},{"DOI":"10.13039\/100006785","name":"Google Research Award","doi-asserted-by":"publisher","id":[{"id":"10.13039\/100006785","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100000001","name":"National Science Foundation","doi-asserted-by":"publisher","award":["CCF-1704624","NeTS-1817205"],"award-info":[{"award-number":["CCF-1704624","NeTS-1817205"]}],"id":[{"id":"10.13039\/100000001","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IEEE Trans. Inform. Theory"],"published-print":{"date-parts":[[2021,12]]},"DOI":"10.1109\/tit.2021.3108952","type":"journal-article","created":{"date-parts":[[2021,8,30]],"date-time":"2021-08-30T21:46:22Z","timestamp":1630359982000},"page":"8248-8263","source":"Crossref","is-referenced-by-count":20,"title":["Geometric Lower Bounds for Distributed Parameter Estimation Under Communication Constraints"],"prefix":"10.1109","volume":"67","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-8335-2364","authenticated-orcid":false,"given":"Yanjun","family":"Han","sequence":"first","affiliation":[]},{"given":"Ayfer","family":"Ozgur","sequence":"additional","affiliation":[]},{"given":"Tsachy","family":"Weissman","sequence":"additional","affiliation":[]}],"member":"263","reference":[{"key":"ref39","doi-asserted-by":"publisher","DOI":"10.4064\/sm-3-1-1-67"},{"key":"ref38","doi-asserted-by":"publisher","DOI":"10.1525\/9780520325883-012"},{"key":"ref33","first-page":"3164","article-title":"Locally private non-asymptotic testing of discrete distributions is faster using interactive mechanisms","volume":"33","author":"berrett","year":"2020","journal-title":"Proc Adv Neural Inf Process Syst"},{"key":"ref32","first-page":"183","article-title":"Pan-private uniformity testing","author":"amin","year":"2020","journal-title":"Proc Conf Learn Theory"},{"key":"ref31","doi-asserted-by":"publisher","DOI":"10.1109\/JSAIT.2020.3039461"},{"key":"ref30","first-page":"1","article-title":"Lower bounds for learning distributions under communication constraints via Fisher information","volume":"21","author":"barnes","year":"2020","journal-title":"J Mach Learn Res"},{"key":"ref37","doi-asserted-by":"publisher","DOI":"10.1007\/978-1-4612-1880-7_29"},{"key":"ref36","volume":"16","author":"ibragimov","year":"2013","journal-title":"Statistical Estimation Asymptotic Theory"},{"key":"ref35","article-title":"Unified lower bounds for interactive high-dimensional estimation under information constraints","author":"acharya","year":"2020","journal-title":"arXiv 2010 06562"},{"key":"ref34","article-title":"Interactive inference under information constraints","author":"acharya","year":"2020","journal-title":"arXiv 2007 10976"},{"key":"ref28","first-page":"41","article-title":"Distributed signal detection under communication constraints","author":"acharya","year":"2020","journal-title":"Proc Conf Learn Theory"},{"key":"ref27","first-page":"3","article-title":"Domain compression and its application to randomness-optimal distributed goodness-of-fit","author":"acharya","year":"2020","journal-title":"Proc Conf Learn Theory"},{"key":"ref29","first-page":"1161","article-title":"Lower bounds for locally private estimation via communication complexity","author":"duchi","year":"2019","journal-title":"Proc Conf Learn Theory"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.1561\/2200000016"},{"key":"ref1","first-page":"3163","article-title":"Geometric lower bounds for distributed parameter estimation under communication constraints","author":"han","year":"2018","journal-title":"Proc Conf Learn Theory (COLT)"},{"key":"ref20","doi-asserted-by":"publisher","DOI":"10.1109\/ISIT.2018.8437818"},{"key":"ref22","first-page":"51","article-title":"Communication complexity in locally private distribution estimation and heavy hitters","author":"acharya","year":"2019","journal-title":"Proc Int Conf Mach Learn"},{"key":"ref21","first-page":"1120","article-title":"Hadamard response: Estimating distributions privately, efficiently, and with little communication","author":"acharya","year":"2019","journal-title":"Proc 22nd Int Conf Artif Intell Statist"},{"key":"ref24","doi-asserted-by":"publisher","DOI":"10.1109\/TIT.2020.3028439"},{"key":"ref23","doi-asserted-by":"publisher","DOI":"10.1109\/TIT.2020.3028440"},{"key":"ref26","doi-asserted-by":"publisher","DOI":"10.1109\/JSAIT.2021.3053569"},{"key":"ref25","first-page":"3312","article-title":"Breaking the communication-privacy-accuracy trilemma","volume":"33","author":"chen","year":"2020","journal-title":"Proc Adv Neural Inf Process Syst"},{"key":"ref50","doi-asserted-by":"publisher","DOI":"10.1090\/surv\/089"},{"key":"ref51","doi-asserted-by":"publisher","DOI":"10.1109\/TIT.2011.2162270"},{"key":"ref56","first-page":"7687","article-title":"On Bayes risk lower bounds","volume":"17","author":"chen","year":"2016","journal-title":"J Mach Learn Res"},{"key":"ref55","article-title":"Distance-based and continuum Fano inequalities with applications to statistical estimation","author":"duchi","year":"2013","journal-title":"arXiv 1311 2669"},{"key":"ref54","doi-asserted-by":"publisher","DOI":"10.1109\/TIT.2008.928987"},{"key":"ref53","doi-asserted-by":"publisher","DOI":"10.1109\/TIT.1973.1055108"},{"key":"ref52","doi-asserted-by":"publisher","DOI":"10.1017\/CBO9780511813603"},{"key":"ref10","first-page":"2328","article-title":"Information-theoretic lower bounds for distributed statistical estimation with communication constraints","author":"zhang","year":"2013","journal-title":"Proc Adv Neural Inf Process Syst"},{"key":"ref11","first-page":"163","article-title":"Fundamental limits of online and distributed algorithms for statistical learning and estimation","author":"shamir","year":"2014","journal-title":"Proc Adv Neural Inf Process Syst"},{"key":"ref40","article-title":"Introduction to the non-asymptotic analysis of random matrices","author":"vershynin","year":"2010","journal-title":"arXiv 1011 3027"},{"key":"ref12","first-page":"2726","article-title":"On communication cost of distributed statistical estimation and dimensionality","author":"garg","year":"2014","journal-title":"Proc Adv Neural Inf Process Syst"},{"key":"ref13","doi-asserted-by":"publisher","DOI":"10.1145\/2897518.2897582"},{"key":"ref14","doi-asserted-by":"publisher","DOI":"10.1109\/TIT.2016.2646342"},{"key":"ref15","first-page":"429","article-title":"Local privacy and statistical minimax rates","author":"duchi","year":"2013","journal-title":"Proc IEEE Ann Symp Foundations of Computer Science (FOCS)"},{"key":"ref16","first-page":"2436","article-title":"Discrete distribution estimation under local privacy","author":"kairouz","year":"2016","journal-title":"Proc Int Conf Mach Learn"},{"key":"ref17","doi-asserted-by":"publisher","DOI":"10.1080\/01621459.2017.1389735"},{"key":"ref18","doi-asserted-by":"publisher","DOI":"10.1109\/TIT.2018.2809790"},{"key":"ref19","first-page":"6394","article-title":"Communication-efficient distributed learning of discrete distributions","author":"diakonikolas","year":"2017","journal-title":"Proc Adv Neural Inf Process Syst"},{"key":"ref4","first-page":"282","article-title":"Protocols for learning classifiers on distributed data","author":"daume","year":"2012","journal-title":"Artificial Intelligence and Statistics"},{"key":"ref3","first-page":"1","article-title":"Distributed learning, communication complexity and privacy","author":"balcan","year":"2012","journal-title":"Proc Conf Learn Theory"},{"key":"ref6","first-page":"165","article-title":"Optimal distributed online prediction using mini-batches","volume":"13","author":"dekel","year":"2012","journal-title":"J Mach Learn Res"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-642-34106-9_15"},{"key":"ref8","article-title":"Advances and open problems in federated learning","author":"kairouz","year":"2019","journal-title":"arXiv 1912 04977"},{"key":"ref7","first-page":"1273","article-title":"Communication-efficient learning of deep networks from decentralized data","author":"mcmahan","year":"2017","journal-title":"Artificial Intelligence and Statistics"},{"key":"ref49","doi-asserted-by":"publisher","DOI":"10.1007\/b13794"},{"journal-title":"Communication Complexity","year":"1997","author":"kushilevitz","key":"ref9"},{"key":"ref46","doi-asserted-by":"publisher","DOI":"10.1016\/j.jcss.2003.11.006"},{"key":"ref45","doi-asserted-by":"publisher","DOI":"10.1007\/BF00533669"},{"journal-title":"Lecture 8 Multiple Hypothesis Testing Tree Fano and Assouad","year":"2019","author":"han","key":"ref48"},{"key":"ref47","first-page":"1021","article-title":"Deux remarques sur l&#x2019;estimation","volume":"296","author":"assouad","year":"1983","journal-title":"Comp Rendus Math Acad Sci Paris"},{"key":"ref42","article-title":"Protection against reconstruction and its applications in private federated learning","author":"bhowmick","year":"2018","journal-title":"arXiv 1812 00984"},{"key":"ref41","article-title":"Minimax bounds for distributed logistic regression","author":"barnes","year":"2019","journal-title":"arXiv 1910 01625"},{"key":"ref44","article-title":"Breaking the dimension dependence in sparse distribution estimation under communication constraints","author":"chen","year":"2021","journal-title":"arXiv 2106 08597"},{"key":"ref43","article-title":"Estimating sparse discrete distributions under local privacy and communication constraints","author":"acharya","year":"2020","journal-title":"arXiv 2011 00083"}],"container-title":["IEEE Transactions on Information Theory"],"original-title":[],"link":[{"URL":"https:\/\/ieeexplore.ieee.org\/ielam\/18\/9622121\/9525382-aam.pdf","content-type":"application\/pdf","content-version":"am","intended-application":"syndication"},{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/18\/9622121\/09525382.pdf?arnumber=9525382","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,5,10]],"date-time":"2022-05-10T14:54:23Z","timestamp":1652194463000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/9525382\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2021,12]]},"references-count":56,"journal-issue":{"issue":"12"},"URL":"https:\/\/doi.org\/10.1109\/tit.2021.3108952","relation":{},"ISSN":["0018-9448","1557-9654"],"issn-type":[{"type":"print","value":"0018-9448"},{"type":"electronic","value":"1557-9654"}],"subject":[],"published":{"date-parts":[[2021,12]]}}}