{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,25]],"date-time":"2025-10-25T14:18:44Z","timestamp":1761401924850,"version":"3.37.3"},"reference-count":25,"publisher":"Institute of Electrical and Electronics Engineers (IEEE)","issue":"2","license":[{"start":{"date-parts":[[2019,6,1]],"date-time":"2019-06-01T00:00:00Z","timestamp":1559347200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/ieeexplore.ieee.org\/Xplorehelp\/downloads\/license-information\/IEEE.html"},{"start":{"date-parts":[[2019,6,1]],"date-time":"2019-06-01T00:00:00Z","timestamp":1559347200000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2019,6,1]],"date-time":"2019-06-01T00:00:00Z","timestamp":1559347200000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"}],"funder":[{"name":"Fox Young Scholars"},{"name":"Fox School PhD Student Research Award"},{"name":"ASA Section on Nonparametric"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IEEE Trans. Big Data"],"published-print":{"date-parts":[[2019,6,1]]},"DOI":"10.1109\/tbdata.2018.2810187","type":"journal-article","created":{"date-parts":[[2018,2,27]],"date-time":"2018-02-27T19:26:51Z","timestamp":1519759611000},"page":"166-179","source":"Crossref","is-referenced-by-count":11,"title":["Nonparametric Distributed Learning Architecture for Big Data: Algorithm and Applications"],"prefix":"10.1109","volume":"5","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-7904-4211","authenticated-orcid":false,"given":"Scott","family":"Bruce","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0305-6240","authenticated-orcid":false,"given":"Zeda","family":"Li","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-5622-4191","authenticated-orcid":false,"given":"Hsiang-Chieh","family":"Yang","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6841-0132","authenticated-orcid":false,"given":"Subhadeep","family":"Mukhopadhyay","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"263","reference":[{"key":"ref10","first-page":"3321","article-title":"Communication-efficient algorithms for statistical optimization","volume":"14","author":"zhang","year":"2013","journal-title":"J Mach Learn Res"},{"key":"ref11","first-page":"1795","article-title":"Bootstrap model aggregation for distributed statistical learning","author":"han","year":"2016","journal-title":"Proc Advances Neural Inf Process Syst"},{"key":"ref12","doi-asserted-by":"publisher","DOI":"10.4310\/SII.2011.v4.n1.a8"},{"key":"ref13","first-page":"1655","article-title":"A split-and-conquer approach for analysis of extraordinarily large data","volume":"24","author":"chen","year":"2014","journal-title":"Statistica Sinica"},{"key":"ref14","doi-asserted-by":"publisher","DOI":"10.1002\/sim.1186"},{"journal-title":"Statistical Methods for Meta-Analysis","year":"1985","author":"hedges","key":"ref15"},{"key":"ref16","doi-asserted-by":"publisher","DOI":"10.1002\/sim.2934"},{"key":"ref17","doi-asserted-by":"publisher","DOI":"10.1111\/1467-9469.00285"},{"key":"ref18","doi-asserted-by":"publisher","DOI":"10.1214\/009053604000001084"},{"key":"ref19","doi-asserted-by":"publisher","DOI":"10.1111\/insr.12000"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.1214\/17-EJS1229"},{"article-title":"LP approach to statistical modeling","year":"2014","author":"mukhopadhyay","key":"ref3"},{"key":"ref6","first-page":"137","article-title":"MapReduce: Simplified data processing on large clusters","author":"dean","year":"2004","journal-title":"Proc 6th Conf Symp Opearting Syst Des Implementation"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.2307\/2371268"},{"key":"ref8","doi-asserted-by":"publisher","DOI":"10.1002\/sam.11242"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.1002\/sta4.7"},{"article-title":"LP mixed data science: Outline of theory","year":"2013","author":"parzen","key":"ref2"},{"key":"ref9","doi-asserted-by":"publisher","DOI":"10.1111\/rssb.12050"},{"year":"2013","key":"ref1","article-title":"Personalize expedia hotel searches - ICDM 2013"},{"key":"ref20","doi-asserted-by":"publisher","DOI":"10.1111\/insr.12005"},{"key":"ref22","doi-asserted-by":"publisher","DOI":"10.1016\/0197-2456(86)90046-2"},{"key":"ref21","doi-asserted-by":"publisher","DOI":"10.1198\/jasa.2011.tm09803"},{"year":"2013","key":"ref24","article-title":"Winners&#x2019; presentation, Personalize Expedia hotel searches competition"},{"key":"ref23","doi-asserted-by":"publisher","DOI":"10.1111\/insr.12002"},{"article-title":"United statistical algorithm, small and big data: Future of statisticians","year":"2013","author":"parzen","key":"ref25"}],"container-title":["IEEE Transactions on Big Data"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/6687317\/8726180\/08303780.pdf?arnumber=8303780","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,7,13]],"date-time":"2022-07-13T20:55:28Z","timestamp":1657745728000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/8303780\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2019,6,1]]},"references-count":25,"journal-issue":{"issue":"2"},"URL":"https:\/\/doi.org\/10.1109\/tbdata.2018.2810187","relation":{},"ISSN":["2332-7790","2372-2096"],"issn-type":[{"type":"electronic","value":"2332-7790"},{"type":"electronic","value":"2372-2096"}],"subject":[],"published":{"date-parts":[[2019,6,1]]}}}