{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,11,18]],"date-time":"2025-11-18T09:25:09Z","timestamp":1763457909353,"version":"3.28.0"},"reference-count":10,"publisher":"IEEE","license":[{"start":{"date-parts":[[2020,8,1]],"date-time":"2020-08-01T00:00:00Z","timestamp":1596240000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/ieeexplore.ieee.org\/Xplorehelp\/downloads\/license-information\/IEEE.html"},{"start":{"date-parts":[[2020,8,1]],"date-time":"2020-08-01T00:00:00Z","timestamp":1596240000000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2020,8,1]],"date-time":"2020-08-01T00:00:00Z","timestamp":1596240000000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2020,8]]},"DOI":"10.1109\/aicas48895.2020.9073802","type":"proceedings-article","created":{"date-parts":[[2020,4,24]],"date-time":"2020-04-24T01:16:57Z","timestamp":1587691017000},"page":"188-192","source":"Crossref","is-referenced-by-count":10,"title":["Online Extreme Learning Machine Design for the Application of Federated Learning"],"prefix":"10.1109","author":[{"given":"Yi-Ta","family":"Chen","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yu-Chuan","family":"Chuang","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"An-Yeu Andy","family":"Wu","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"263","reference":[{"key":"ref4","doi-asserted-by":"crossref","first-page":"489","DOI":"10.1016\/j.neucom.2005.12.126","article-title":"Extreme learning machine: theory and applications","volume":"70","author":"huang","year":"2006","journal-title":"Neurocomputing"},{"key":"ref3","article-title":"Communication-efficient learning of deep networks from decentralized data","author":"mcmahan","year":"2016","journal-title":"arXiv preprint arXiv 1602 05629"},{"key":"ref10","article-title":"Federated learning: Strategies for improving communication efficiency","author":"konecny","year":"2016","journal-title":"arXiv preprint arXiv 1610 05492"},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.1109\/ISCAS.2018.8350948"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.1109\/TNN.2006.880583"},{"key":"ref8","doi-asserted-by":"publisher","DOI":"10.1109\/SiPS47522.2019.9020609"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.1109\/TCSI.2019.2940642"},{"key":"ref2","article-title":"Federated learning with non-iid data","author":"zhao","year":"2018","journal-title":"arXivpreprint arXiv 1806 00582"},{"key":"ref9","doi-asserted-by":"publisher","DOI":"10.1109\/5.726791"},{"key":"ref1","article-title":"Federated optimization: Distributed optimization beyond the datacenter","author":"kone?n\u00fd","year":"2015","journal-title":"arXiv preprint arXiv 1511 05271"}],"event":{"name":"2020 2nd IEEE International Conference on Artificial Intelligence Circuits and Systems (AICAS)","start":{"date-parts":[[2020,8,31]]},"location":"Genova, Italy","end":{"date-parts":[[2020,9,2]]}},"container-title":["2020 2nd IEEE International Conference on Artificial Intelligence Circuits and Systems (AICAS)"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/9066468\/9072687\/09073802.pdf?arnumber=9073802","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,6,27]],"date-time":"2022-06-27T15:46:52Z","timestamp":1656344812000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/9073802\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2020,8]]},"references-count":10,"URL":"https:\/\/doi.org\/10.1109\/aicas48895.2020.9073802","relation":{},"subject":[],"published":{"date-parts":[[2020,8]]}}}