{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,2]],"date-time":"2026-07-02T01:34:49Z","timestamp":1782956089382,"version":"3.54.5"},"reference-count":12,"publisher":"IEEE","license":[{"start":{"date-parts":[[2024,6,9]],"date-time":"2024-06-09T00:00:00Z","timestamp":1717891200000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2024,6,9]],"date-time":"2024-06-09T00:00:00Z","timestamp":1717891200000},"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":[[2024,6,9]]},"DOI":"10.1109\/iccworkshops59551.2024.10615720","type":"proceedings-article","created":{"date-parts":[[2024,8,12]],"date-time":"2024-08-12T17:23:42Z","timestamp":1723483422000},"page":"1352-1358","source":"Crossref","is-referenced-by-count":14,"title":["FedGreen: Carbon-Aware Federated Learning with Model Size Adaptation"],"prefix":"10.1109","author":[{"given":"Ali","family":"Abbasi","sequence":"first","affiliation":[{"name":"University of Calgary,Department of Electrical and Software Engineering,Calgary,AB,Canada"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Fan","family":"Dong","sequence":"additional","affiliation":[{"name":"University of Calgary,Department of Electrical and Software Engineering,Calgary,AB,Canada"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Xin","family":"Wang","sequence":"additional","affiliation":[{"name":"University of Calgary,Department of Geomatics Engineering,Calgary,AB,Canada"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Henry","family":"Leung","sequence":"additional","affiliation":[{"name":"University of Calgary,Department of Electrical and Software Engineering,Calgary,AB,Canada"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jiayu","family":"Zhou","sequence":"additional","affiliation":[{"name":"Michigan State University,Department of Computer Science and Engineering,East Lansing,MI,USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Steve","family":"Drew","sequence":"additional","affiliation":[{"name":"University of Calgary,Department of Electrical and Software Engineering,Calgary,AB,Canada"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"263","reference":[{"key":"ref1","doi-asserted-by":"publisher","DOI":"10.1016\/j.susoc.2021.10.001"},{"key":"ref2","article-title":"A first look into the carbon foot-print of federated learning","author":"Qiu","year":"2021","journal-title":"arXiv preprint"},{"key":"ref3","first-page":"12876","article-title":"Fjord: Fair and accurate federated learning under heterogeneous targets with ordered dropout","volume":"34","author":"Horvath","year":"2021","journal-title":"Advances in Neural Information Processing Systems"},{"key":"ref4","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":"ref5","article-title":"Heterofl: Computation and communication efficient federated learning for het-erogeneous clients","author":"Diao","year":"2020","journal-title":"arXiv preprint"},{"key":"ref6","first-page":"4270","article-title":"Resource-adaptive federated learning with all-in-one neural composition","volume":"35","author":"Mei","year":"2022","journal-title":"Advances in Neural Information Processing Systems"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.1109\/TNNLS.2022.3166101"},{"key":"ref8","doi-asserted-by":"publisher","DOI":"10.1109\/MNET.127.2200388"},{"key":"ref9","doi-asserted-by":"publisher","DOI":"10.1109\/INFOCOM53939.2023.10229017"},{"issue":"1","key":"ref10","first-page":"1929","article-title":"Dropout: a simple way to pre-vent neural networks from overfitting","volume":"15","author":"Srivastava","year":"2014","journal-title":"The journal of machine learning research"},{"key":"ref11","article-title":"Slimmable neural networks","author":"Yu","year":"2018","journal-title":"arXiv preprint"},{"key":"ref12","doi-asserted-by":"publisher","DOI":"10.1109\/IJCNN.2017.7966217"}],"event":{"name":"2024 IEEE International Conference on Communications Workshops (ICC Workshops)","location":"Denver, CO, USA","start":{"date-parts":[[2024,6,9]]},"end":{"date-parts":[[2024,6,13]]}},"container-title":["2024 IEEE International Conference on Communications Workshops (ICC Workshops)"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx8\/10615255\/10615259\/10615720.pdf?arnumber=10615720","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,8,13]],"date-time":"2024-08-13T05:25:08Z","timestamp":1723526708000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/10615720\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024,6,9]]},"references-count":12,"URL":"https:\/\/doi.org\/10.1109\/iccworkshops59551.2024.10615720","relation":{},"subject":[],"published":{"date-parts":[[2024,6,9]]}}}