{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2024,9,7]],"date-time":"2024-09-07T17:29:11Z","timestamp":1725730151230},"reference-count":16,"publisher":"IEEE","license":[{"start":{"date-parts":[[2023,11,17]],"date-time":"2023-11-17T00:00:00Z","timestamp":1700179200000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2023,11,17]],"date-time":"2023-11-17T00:00:00Z","timestamp":1700179200000},"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","id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2023,11,17]]},"DOI":"10.1109\/ipccc59175.2023.10253887","type":"proceedings-article","created":{"date-parts":[[2023,10,18]],"date-time":"2023-10-18T17:44:32Z","timestamp":1697651072000},"page":"430-435","source":"Crossref","is-referenced-by-count":1,"title":["Bi-level Sampling: Improved Clients Selection in Heterogeneous Settings for Federated Learning"],"prefix":"10.1109","volume":"2022","author":[{"given":"Danyang","family":"Xiao","sequence":"first","affiliation":[{"name":"Sun Yat-sen University"}]},{"given":"Congcong","family":"Zhan","sequence":"additional","affiliation":[{"name":"Sun Yat-sen University"}]},{"given":"Jialun","family":"Li","sequence":"additional","affiliation":[{"name":"Sun Yat-sen University"}]},{"given":"Weigang","family":"Wu","sequence":"additional","affiliation":[{"name":"Sun Yat-sen University"}]}],"member":"263","reference":[{"article-title":"Communication-efficient learning of deep networks from decentralized data","volume-title":"Proceedings of the 20th International Conference on Artificial Intelligence and Statistics (AISTATS 2017)","author":"McMahan","key":"ref1"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.1561\/2200000083"},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.1109\/TPDS.2023.3277423"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.1109\/JSAC.2023.3273700"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.1016\/j.ins.2020.05.121"},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.1109\/TWC.2022.3201207"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.1109\/TPDS.2021.3134647"},{"key":"ref8","doi-asserted-by":"publisher","DOI":"10.1109\/JIOT.2022.3161943"},{"key":"ref9","doi-asserted-by":"publisher","DOI":"10.1016\/j.jpdc.2023.03.003"},{"article-title":"Federated optimization in heterogeneous networks","volume-title":"Proceedings of Machine Learning and Systems 2020 (MLSys 2020)","author":"Li","key":"ref10"},{"article-title":"Tighter theory for local SGD on identical and heterogeneous data","volume-title":"The 23rd International Conference on Artificial Intelligence and Statistics (AISTATS 2020)","author":"Khaled","key":"ref11"},{"article-title":"Clustered sampling: Low-variance and improved representativity for clients selection in federated learning","volume-title":"Proceedings of the 38th International Conference on Machine Learning (ICML2021)","author":"Fraboni","key":"ref12"},{"article-title":"On the convergence of fedavg on non-iid data","volume-title":"8th International Conference on Learning Representations (ICLR 2020)","author":"Li","key":"ref13"},{"issue":"1","key":"ref14","first-page":"1","article-title":"Optimal client sampling for federated learning","volume":"2022","author":"Chen","year":"2022","journal-title":"Transactions on Machine Learning Research"},{"key":"ref15","doi-asserted-by":"publisher","DOI":"10.1109\/ICC.2019.8761315"},{"key":"ref16","article-title":"Measuring the effects of non-identical data distribution for federated visual classification","author":"Hsu","year":"2019","journal-title":"arXiv preprint arXiv:1909.06335"}],"event":{"name":"2023 IEEE International Performance, Computing, and Communications Conference (IPCCC)","start":{"date-parts":[[2023,11,17]]},"location":"Anaheim, CA, USA","end":{"date-parts":[[2023,11,19]]}},"container-title":["2023 IEEE International Performance, Computing, and Communications Conference (IPCCC)"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/10253817\/10253818\/10253887.pdf?arnumber=10253887","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,3,2]],"date-time":"2024-03-02T02:37:13Z","timestamp":1709347033000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/10253887\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023,11,17]]},"references-count":16,"URL":"https:\/\/doi.org\/10.1109\/ipccc59175.2023.10253887","relation":{},"subject":[],"published":{"date-parts":[[2023,11,17]]}}}