{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,26]],"date-time":"2026-03-26T15:53:24Z","timestamp":1774540404603,"version":"3.50.1"},"reference-count":17,"publisher":"IEEE","license":[{"start":{"date-parts":[[2022,11,26]],"date-time":"2022-11-26T00:00:00Z","timestamp":1669420800000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2022,11,26]],"date-time":"2022-11-26T00:00:00Z","timestamp":1669420800000},"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":[[2022,11,26]]},"DOI":"10.1109\/iscmi56532.2022.10068456","type":"proceedings-article","created":{"date-parts":[[2023,3,21]],"date-time":"2023-03-21T15:49:06Z","timestamp":1679413746000},"page":"62-67","source":"Crossref","is-referenced-by-count":5,"title":["A Novel Approach for Federated Learning with Non-IID Data"],"prefix":"10.1109","author":[{"given":"Hiep","family":"Nguyen","sequence":"first","affiliation":[{"name":"HCL Technologies,Vietnam"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Harikrishna","family":"Warrier","sequence":"additional","affiliation":[{"name":"HCL Technologies,India"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yogesh","family":"Gupta","sequence":"additional","affiliation":[{"name":"HCL Technologies,India"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"263","reference":[{"key":"ref13","doi-asserted-by":"publisher","DOI":"10.1109\/ISIT45174.2021.9517850"},{"key":"ref12","first-page":"1273","article-title":"Communication-efficient learning of deep networks from decentralized data","volume":"54","author":"mcmahan","year":"2017","journal-title":"Proceedings of the 20th International Conference on Artificial Intelligence and Statistics AISTATS 2017"},{"key":"ref15","article-title":"Tackling the objective inconsistency problem in heterogeneous federated optimization","author":"wang","year":"2020","journal-title":"Advances in Neural Information Processing Systems 33 Annual Conference on Neural Information Processing Systems 2020 NeurIPS 2020"},{"key":"ref14","article-title":"Adaptive federated optimization","author":"reddi","year":"2021","journal-title":"9th International Conference on Learning Representations ICLR 2021"},{"key":"ref11","article-title":"Variance reduced local SGD with lower communication complexity","volume":"abs 1912 12844","author":"liang","year":"2019","journal-title":"CoRR"},{"key":"ref10","article-title":"On the convergence of fedavg on non-iid data","author":"li","year":"2020","journal-title":"8th International Conference on Learning Representations ICLR 2020"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR52688.2022.00987"},{"key":"ref1","article-title":"Flower: A friendly federated learning research framework","volume":"abs 2007 14390","author":"beutel","year":"2020","journal-title":"CoRR"},{"key":"ref17","article-title":"Federated learning with non-iid data","volume":"abs 1806 582","author":"zhao","year":"2018","journal-title":"CoRR"},{"key":"ref16","article-title":"Slowmo: Improving communication-efficient distributed SGD with slow momentum","author":"wang","year":"2020","journal-title":"8th International Conference on Learning Representations ICLR 2020"},{"key":"ref8","article-title":"Federated optimization in heterogeneous networks","author":"li","year":"2020","journal-title":"Proceedings of Machine Learning and Systems 2020 MLSys 2020"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR46437.2021.01057"},{"key":"ref9","article-title":"Fair resource allocation in federated learning","author":"li","year":"2020","journal-title":"8th International Conference on Learning Representations ICLR 2020"},{"key":"ref4","article-title":"Mime: Mimicking centralized stochastic algorithms in federated learning","volume":"abs 2008 3606","author":"karimireddy","year":"2020","journal-title":"CoRR"},{"key":"ref3","article-title":"Measuring the effects of non-identical data distribution for federated visual classification","volume":"abs 1909 6335","author":"hsu","year":"2019","journal-title":"CoRR"},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.1109\/ICDE53745.2022.00077"},{"key":"ref5","first-page":"5132","article-title":"SCAFFOLD: stochastic controlled averaging for federated learning","volume":"119","author":"karimireddy","year":"2020","journal-title":"Proceedings of the 37th International Conference on Machine Learning ICML 2020"}],"event":{"name":"2022 9th International Conference on Soft Computing & Machine Intelligence (ISCMI)","location":"Toronto, ON, Canada","start":{"date-parts":[[2022,11,26]]},"end":{"date-parts":[[2022,11,27]]}},"container-title":["2022 9th International Conference on Soft Computing & Machine Intelligence (ISCMI)"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/10068346\/10068435\/10068456.pdf?arnumber=10068456","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2023,4,10]],"date-time":"2023-04-10T14:57:18Z","timestamp":1681138638000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/10068456\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022,11,26]]},"references-count":17,"URL":"https:\/\/doi.org\/10.1109\/iscmi56532.2022.10068456","relation":{},"subject":[],"published":{"date-parts":[[2022,11,26]]}}}