{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,22]],"date-time":"2026-01-22T07:56:53Z","timestamp":1769068613718,"version":"3.49.0"},"reference-count":49,"publisher":"Institute of Electrical and Electronics Engineers (IEEE)","issue":"5","license":[{"start":{"date-parts":[[2023,5,1]],"date-time":"2023-05-01T00:00:00Z","timestamp":1682899200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/ieeexplore.ieee.org\/Xplorehelp\/downloads\/license-information\/IEEE.html"},{"start":{"date-parts":[[2023,5,1]],"date-time":"2023-05-01T00:00:00Z","timestamp":1682899200000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2023,5,1]],"date-time":"2023-05-01T00:00:00Z","timestamp":1682899200000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["62036006"],"award-info":[{"award-number":["62036006"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100000923","name":"Australian Research Council","doi-asserted-by":"publisher","award":["LP180100114"],"award-info":[{"award-number":["LP180100114"]}],"id":[{"id":"10.13039\/501100000923","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100000923","name":"Australian Research Council","doi-asserted-by":"publisher","award":["DP200102611"],"award-info":[{"award-number":["DP200102611"]}],"id":[{"id":"10.13039\/501100000923","id-type":"DOI","asserted-by":"publisher"}]},{"name":"A*STAR Centre for Frontier AI Research (CFAR) and the Data Science Artificial Intelligence Research Center (DSAIR) at School of Computer Science and Engineering, Nanyang Technological University"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IEEE Trans. Cybern."],"published-print":{"date-parts":[[2023,5]]},"DOI":"10.1109\/tcyb.2021.3139076","type":"journal-article","created":{"date-parts":[[2022,1,19]],"date-time":"2022-01-19T20:31:35Z","timestamp":1642624295000},"page":"2955-2968","source":"Crossref","is-referenced-by-count":13,"title":["Multiparty Dual Learning"],"prefix":"10.1109","volume":"53","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-2990-9205","authenticated-orcid":false,"given":"Yuan","family":"Gao","sequence":"first","affiliation":[{"name":"School of Electronic Engineering, Key Laboratory of Intelligent Perception and Image Understanding of Ministry of Education, Xidian University, Xi&#x2019;an, Shaanxi, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0415-8556","authenticated-orcid":false,"given":"Maoguo","family":"Gong","sequence":"additional","affiliation":[{"name":"School of Electronic Engineering, Key Laboratory of Intelligent Perception and Image Understanding of Ministry of Education, Xidian University, Xi&#x2019;an, Shaanxi, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3431-0432","authenticated-orcid":false,"given":"Yu","family":"Xie","sequence":"additional","affiliation":[{"name":"Key Laboratory of Computational Intelligence and Chinese Information Processing, Ministry of Education, Shanxi University, Taiyuan, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-6631-1651","authenticated-orcid":false,"given":"A. K.","family":"Qin","sequence":"additional","affiliation":[{"name":"Department of Computing Technologies, Swinburne University of Technology, Hawthorn, VIC, Australia"}]},{"given":"Ke","family":"Pan","sequence":"additional","affiliation":[{"name":"School of Electronic Engineering, Key Laboratory of Intelligent Perception and Image Understanding of Ministry of Education, Xidian University, Xi&#x2019;an, Shaanxi, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4480-169X","authenticated-orcid":false,"given":"Yew-Soon","family":"Ong","sequence":"additional","affiliation":[{"name":"Agency for Science, Technology and Research, and the School of Computer Science and Engineering, Nanyang Technological University, Singapore"}]}],"member":"263","reference":[{"key":"ref13","doi-asserted-by":"publisher","DOI":"10.1145\/2810103.2813687"},{"key":"ref12","doi-asserted-by":"publisher","DOI":"10.1109\/TII.2019.2945367"},{"key":"ref15","first-page":"1","article-title":"Federated adversarial domain adaptation","author":"peng","year":"2020","journal-title":"Proc 8th Int Conf Learn Represent"},{"key":"ref14","doi-asserted-by":"publisher","DOI":"10.1109\/TIFS.2017.2787987"},{"key":"ref11","doi-asserted-by":"publisher","DOI":"10.1109\/TKDE.2009.191"},{"key":"ref10","article-title":"Secure federated transfer learning","author":"liu","year":"2018","journal-title":"arXiv 1812 03337"},{"key":"ref17","article-title":"Private federated learning on vertically partitioned data via entity resolution and additively homomorphic encryption","author":"hardy","year":"2017","journal-title":"arXiv 1711 10677"},{"key":"ref16","doi-asserted-by":"publisher","DOI":"10.1109\/JIOT.2020.2987843"},{"key":"ref19","first-page":"820","article-title":"Dual learning for machine translation","author":"he","year":"2016","journal-title":"Proc Adv Neural Inf Process Syst"},{"key":"ref18","first-page":"3789","article-title":"Dual supervised learning","author":"xia","year":"2017","journal-title":"Proc 34th Int Conf Mach Learn"},{"key":"ref46","author":"dua","year":"2017","journal-title":"UCI Machine Learning Repository"},{"key":"ref45","doi-asserted-by":"publisher","DOI":"10.1016\/j.dss.2014.03.001"},{"key":"ref48","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v33i01.3301346"},{"key":"ref47","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2018.00572"},{"key":"ref42","doi-asserted-by":"publisher","DOI":"10.1145\/775047.775142"},{"key":"ref41","doi-asserted-by":"publisher","DOI":"10.1137\/1.9781611972740.21"},{"key":"ref44","author":"krizhevsky","year":"2009","journal-title":"Learning multiple layers of features from tiny images"},{"key":"ref43","doi-asserted-by":"publisher","DOI":"10.1109\/MSP.2012.2211477"},{"key":"ref49","first-page":"2874","article-title":"Local-aggregation graph networks","volume":"42","author":"chang","year":"2020","journal-title":"IEEE Trans Pattern Anal Mach Intell"},{"key":"ref8","doi-asserted-by":"publisher","DOI":"10.1109\/TIFS.2019.2931068"},{"key":"ref7","first-page":"6343","article-title":"Distributed learning without distress: Privacy-preserving empirical risk minimization","author":"jayaraman","year":"2018","journal-title":"Proc Adv Neural Inf Process Syst"},{"key":"ref9","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2018.2836422"},{"key":"ref4","article-title":"Federated reinforcement learning","author":"zhuo","year":"2019","journal-title":"arXiv 1901 08277"},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.1016\/j.neunet.2019.10.001"},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2017.2682082"},{"key":"ref5","first-page":"4424","article-title":"Federated multi-task learning","author":"smith","year":"2017","journal-title":"Proc Adv Neural Inf Process Syst"},{"key":"ref40","doi-asserted-by":"publisher","DOI":"10.1109\/TNNLS.2015.2424995"},{"key":"ref35","article-title":"ADADELTA: An adaptive learning rate method","author":"zeiler","year":"2012","journal-title":"arXiv 1212 5701"},{"key":"ref34","first-page":"2595","article-title":"Parallelized stochastic gradient descent","author":"zinkevich","year":"2010","journal-title":"Proc Adv Neural Inf Process Syst"},{"key":"ref37","article-title":"VAFL: A method of vertical asynchronous federated learning","author":"chen","year":"2020","journal-title":"arXiv 2007 06081"},{"key":"ref36","first-page":"2545","article-title":"Variants of RMSProp and adagrad with logarithmic regret bounds","author":"mukkamala","year":"2017","journal-title":"Proc 34th Int Conf Mach Learn"},{"key":"ref31","doi-asserted-by":"publisher","DOI":"10.1145\/1247480.1247553"},{"key":"ref30","doi-asserted-by":"publisher","DOI":"10.1109\/ICDM.2017.48"},{"key":"ref33","doi-asserted-by":"publisher","DOI":"10.1214\/10-AOS799"},{"key":"ref32","doi-asserted-by":"publisher","DOI":"10.1109\/INFOCOM.2017.8057178"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.1145\/3298981"},{"key":"ref1","doi-asserted-by":"publisher","DOI":"10.1145\/3133956.3133982"},{"key":"ref39","doi-asserted-by":"publisher","DOI":"10.1145\/2976749.2978318"},{"key":"ref38","doi-asserted-by":"publisher","DOI":"10.1145\/3214303"},{"key":"ref24","doi-asserted-by":"publisher","DOI":"10.1109\/TCYB.2018.2877410"},{"key":"ref23","doi-asserted-by":"publisher","DOI":"10.1109\/ICDE.2019.00063"},{"key":"ref26","doi-asserted-by":"publisher","DOI":"10.1109\/TCYB.2019.2948427"},{"key":"ref25","doi-asserted-by":"publisher","DOI":"10.1016\/j.ins.2018.10.024"},{"key":"ref20","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2017.310"},{"key":"ref22","first-page":"5383","article-title":"Model-level dual learning","author":"xia","year":"2018","journal-title":"Proc 35th Int Conf Mach Learn"},{"key":"ref21","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2017.296"},{"key":"ref28","article-title":"Performance analysis and optimization in privacy-preserving federated learning","author":"wei","year":"2020","journal-title":"arXiv 2003 00229"},{"key":"ref27","doi-asserted-by":"publisher","DOI":"10.1109\/TIFS.2020.2988575"},{"key":"ref29","doi-asserted-by":"publisher","DOI":"10.1007\/11681878_14"}],"container-title":["IEEE Transactions on Cybernetics"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/6221036\/10106628\/09686623.pdf?arnumber=9686623","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2023,5,8]],"date-time":"2023-05-08T18:59:34Z","timestamp":1683572374000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/9686623\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023,5]]},"references-count":49,"journal-issue":{"issue":"5"},"URL":"https:\/\/doi.org\/10.1109\/tcyb.2021.3139076","relation":{},"ISSN":["2168-2267","2168-2275"],"issn-type":[{"value":"2168-2267","type":"print"},{"value":"2168-2275","type":"electronic"}],"subject":[],"published":{"date-parts":[[2023,5]]}}}