{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,6]],"date-time":"2026-02-06T02:47:11Z","timestamp":1770346031793,"version":"3.49.0"},"reference-count":31,"publisher":"IEEE","license":[{"start":{"date-parts":[[2024,6,19]],"date-time":"2024-06-19T00:00:00Z","timestamp":1718755200000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2024,6,19]],"date-time":"2024-06-19T00:00:00Z","timestamp":1718755200000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"}],"funder":[{"DOI":"10.13039\/100000001","name":"National Science Foundation","doi-asserted-by":"publisher","id":[{"id":"10.13039\/100000001","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100012226","name":"Fundamental Research Funds for the Central Universities","doi-asserted-by":"publisher","id":[{"id":"10.13039\/501100012226","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2024,6,19]]},"DOI":"10.1109\/iwqos61813.2024.10682905","type":"proceedings-article","created":{"date-parts":[[2024,9,26]],"date-time":"2024-09-26T17:41:00Z","timestamp":1727372460000},"page":"1-10","source":"Crossref","is-referenced-by-count":2,"title":["Towards Communication-Efficient Federated Graph Learning: An Adaptive Client Selection Perspective"],"prefix":"10.1109","author":[{"given":"Xianjun","family":"Gao","sequence":"first","affiliation":[{"name":"University of Science and Technology of China,School of Computer Science and Technology"}]},{"given":"Jianchun","family":"Liu","sequence":"additional","affiliation":[{"name":"University of Science and Technology of China,School of Computer Science and Technology"}]},{"given":"Hongli","family":"Xu","sequence":"additional","affiliation":[{"name":"University of Science and Technology of China,School of Computer Science and Technology"}]},{"given":"Qianpiao","family":"Ma","sequence":"additional","affiliation":[{"name":"Purple Mountain Laboratories"}]},{"given":"Lun","family":"Wang","sequence":"additional","affiliation":[{"name":"University of Science and Technology of China,School of Computer Science and Technology"}]}],"member":"263","reference":[{"key":"ref1","doi-asserted-by":"publisher","DOI":"10.1145\/3219819.3219890"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.1109\/TII.2022.3203395"},{"key":"ref3","article-title":"Fedgcn: Convergence and communication tradeoffs in federated training of graph convolutional networks","author":"Yao","year":"2022"},{"key":"ref4","article-title":"Fedgraphnn: A federated learning benchmark system for graph neural networks","volume-title":"ICLR 2021 Workshop on Distributed and Private Machine Learning (DPML)","author":"He"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.1109\/TMC.2024.3373506"},{"key":"ref6","first-page":"1396","article-title":"Personalized subgraph federated learning","volume-title":"International Conference on Machine Learning","author":"Baek"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.1109\/TMC.2024.3370961"},{"key":"ref8","doi-asserted-by":"publisher","DOI":"10.1109\/TMC.2023.3338954"},{"key":"ref9","article-title":"Glasu: A communication-efficient algorithm for federated learning with vertically distributed graph data","author":"Zhang","year":"2023"},{"key":"ref10","doi-asserted-by":"publisher","DOI":"10.1145\/3501815"},{"key":"ref11","article-title":"Fedgnn: Federated graph neural network for privacy-preserving recommendation","author":"Wu","year":"2021"},{"key":"ref12","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v37i8.26187"},{"key":"ref13","article-title":"On the convergence of fedavg on non-iid data","author":"Li","year":"2019"},{"key":"ref14","first-page":"18 839","article-title":"Federated graph classification over non-iid graphs","volume":"34","author":"Xie","year":"2021","journal-title":"Advances in neural information processing systems"},{"key":"ref15","doi-asserted-by":"publisher","DOI":"10.1109\/ACCESS.2021.3056919"},{"key":"ref16","doi-asserted-by":"publisher","DOI":"10.1109\/TMC.2023.3315451"},{"key":"ref17","doi-asserted-by":"publisher","DOI":"10.1145\/2124295.2124309"},{"key":"ref18","article-title":"Semi-supervised classification with graph convolutional networks","author":"Kipf","year":"2016"},{"key":"ref19","doi-asserted-by":"publisher","DOI":"10.1109\/ICDE53745.2022.00015"},{"key":"ref20","doi-asserted-by":"publisher","DOI":"10.1109\/IWQoS54832.2022.9812908"},{"key":"ref21","first-page":"1273","article-title":"Communication-efficient learning of deep networks from decentralized data","volume-title":"Artificial intelligence and statistics","author":"McMahan"},{"key":"ref22","doi-asserted-by":"publisher","DOI":"10.1023\/A:1013689704352"},{"key":"ref23","article-title":"Unifying pac and regret: Uniform pac bounds for episodic reinforcement learning","volume":"30","author":"Dann","year":"2017","journal-title":"Advances in Neural Information Processing Systems"},{"key":"ref24","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-540-39718-2_23"},{"key":"ref25","article-title":"Graph attention networks","author":"Veli\u010dkovi\u0107","year":"2017"},{"key":"ref26","doi-asserted-by":"publisher","DOI":"10.1145\/1458082.1458205"},{"key":"ref27","doi-asserted-by":"publisher","DOI":"10.1145\/1935826.1935877"},{"key":"ref28","doi-asserted-by":"publisher","DOI":"10.1145\/3404835.3463028"},{"key":"ref29","first-page":"10 351","article-title":"Towards understanding biased client selection in federated learning","volume-title":"International Conference on Artificial Intelligence and Statistics","author":"Cho"},{"key":"ref30","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR52688.2022.00986"},{"key":"ref31","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-7908-2604-3_16"}],"event":{"name":"2024 IEEE\/ACM 32nd International Symposium on Quality of Service (IWQoS)","location":"Guangzhou, China","start":{"date-parts":[[2024,6,19]]},"end":{"date-parts":[[2024,6,21]]}},"container-title":["2024 IEEE\/ACM 32nd International Symposium on Quality of Service (IWQoS)"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx8\/10682818\/10682608\/10682905.pdf?arnumber=10682905","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,9,27]],"date-time":"2024-09-27T04:40:23Z","timestamp":1727412023000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/10682905\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024,6,19]]},"references-count":31,"URL":"https:\/\/doi.org\/10.1109\/iwqos61813.2024.10682905","relation":{},"subject":[],"published":{"date-parts":[[2024,6,19]]}}}