{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,31]],"date-time":"2026-03-31T08:59:19Z","timestamp":1774947559943,"version":"3.50.1"},"reference-count":20,"publisher":"IEEE","license":[{"start":{"date-parts":[[2023,10,8]],"date-time":"2023-10-08T00:00:00Z","timestamp":1696723200000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2023,10,8]],"date-time":"2023-10-08T00:00:00Z","timestamp":1696723200000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"}],"funder":[{"DOI":"10.13039\/501100005090","name":"Beijing Nova Program","doi-asserted-by":"publisher","id":[{"id":"10.13039\/501100005090","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2023,10,8]]},"DOI":"10.1109\/icip49359.2023.10222893","type":"proceedings-article","created":{"date-parts":[[2023,9,11]],"date-time":"2023-09-11T17:58:31Z","timestamp":1694455111000},"page":"2300-2304","source":"Crossref","is-referenced-by-count":2,"title":["MDFD: Study of Distributed Non-IID Scenarios and Frechet Distance-Based Evaluation"],"prefix":"10.1109","author":[{"given":"Wei","family":"Wang","sequence":"first","affiliation":[{"name":"Nankai University, Tianjin Key Laboratory of Network and Data Security Technology,Trusted AI Laboratory, College of Computer Science,Tianjin,China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Mingwei","family":"Zhang","sequence":"additional","affiliation":[{"name":"Nankai University, Tianjin Key Laboratory of Network and Data Security Technology,Trusted AI Laboratory, College of Computer Science,Tianjin,China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Ziwen","family":"Wu","sequence":"additional","affiliation":[{"name":"Nankai University, Tianjin Key Laboratory of Network and Data Security Technology,Trusted AI Laboratory, College of Computer Science,Tianjin,China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Qianxi","family":"Chen","sequence":"additional","affiliation":[{"name":"Nankai University, Tianjin Key Laboratory of Network and Data Security Technology,Trusted AI Laboratory, College of Computer Science,Tianjin,China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yue","family":"Li","sequence":"additional","affiliation":[{"name":"Nankai University, Tianjin Key Laboratory of Network and Data Security Technology,Trusted AI Laboratory, College of Computer Science,Tianjin,China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"263","reference":[{"key":"ref1","first-page":"1273","article-title":"Communication-efficient learning of deep networks from decentralized data","volume-title":"Artificial intelligence and statistics.","author":"McMahan","year":"2017"},{"key":"ref2","author":"Kone\u010dn\u1ef3","year":"2016","journal-title":"Federated learning: Strategies for improving communication efficiency"},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.2200\/s00960ed2v01y201910aim043"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.1109\/ICDE53745.2022.00077"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v35i9.16960"},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.1109\/TWC.2021.3108197"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.1145\/3423211.3425688"},{"key":"ref8","author":"Yonetani","year":"2019","journal-title":"Decentralized learning of generative adversarial networks from non-iid data"},{"key":"ref9","doi-asserted-by":"publisher","DOI":"10.1109\/IPDPS.2019.00095"},{"key":"ref10","author":"Rasouli","year":"2020","journal-title":"Fedgan: Federated generative adversarial networks for distributed data"},{"key":"ref11","doi-asserted-by":"publisher","DOI":"10.1109\/ICASSP40776.2020.9054559"},{"key":"ref12","doi-asserted-by":"publisher","DOI":"10.1109\/jiot.2023.3319630"},{"key":"ref13","doi-asserted-by":"publisher","DOI":"10.1016\/j.neucom.2020.07.089"},{"key":"ref14","author":"Paszke","year":"2019","journal-title":"Pytorch: An imperative style, high-performance deep learning library"},{"key":"ref15","doi-asserted-by":"publisher","DOI":"10.1109\/5.726791"},{"key":"ref16","author":"Xiao","year":"2017","journal-title":"Fashion-mnist: a novel image dataset for benchmarking machine learning algorithms"},{"key":"ref17","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2016.308"},{"key":"ref18","author":"Adler","year":"2018","journal-title":"Banach wasserstein gan"},{"key":"ref19","article-title":"Gans trained by a two time-scale update rule converge to a local nash equilibrium","volume":"30","author":"Heusel","year":"2017","journal-title":"Advances in neural information processing systems"},{"key":"ref20","author":"Barratt","year":"2018","journal-title":"A note on the inception score"}],"event":{"name":"2023 IEEE International Conference on Image Processing (ICIP)","location":"Kuala Lumpur, Malaysia","start":{"date-parts":[[2023,10,8]]},"end":{"date-parts":[[2023,10,11]]}},"container-title":["2023 IEEE International Conference on Image Processing (ICIP)"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/10221937\/10221892\/10222893.pdf?arnumber=10222893","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,3,1]],"date-time":"2024-03-01T20:46:48Z","timestamp":1709326008000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/10222893\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023,10,8]]},"references-count":20,"URL":"https:\/\/doi.org\/10.1109\/icip49359.2023.10222893","relation":{},"subject":[],"published":{"date-parts":[[2023,10,8]]}}}