On the convergence of fedavg on non-iid
WebIn this setting, local models might be strayed far from the local optimum of the complete dataset, thus possibly hindering the convergence of the federated model. Several Federated Learning algorithms, such as FedAvg, FedProx and Federated Curvature (FedCurv), aiming at tackling the non-IID setting, have already been proposed. WebIn this setting, local models might be strayed far from the local optimum of the complete dataset, thus possibly hindering the convergence of the federated model. Several …
On the convergence of fedavg on non-iid
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Web31 de out. de 2024 · On the Convergence of FedAvg on Non-IID Data. Xiang Li, Kaixuan Huang, Wenhao Yang, Shusen Wang, Zhihua Zhang; Computer Science. ICLR. 2024; TLDR. This paper analyzes the convergence of Federated Averaging on non-iid data and establishes a convergence rate of $\mathcal{O}(\frac{1}{T})$ for strongly convex and … Web17 de mar. de 2024 · On the convergence of fedavg on non-iid data. In International Conference on Learning Representations, 2024. 1 Ensemble distillation for robust model fusion in federated learning
Web7 de mai. de 2024 · It dynamically accelerates convergence on non-IID data and resists performance deterioration caused by the staleness effect simultaneously using a two-phase training mechanism. Theoretical analysis and experimental results prove that our approach converges faster with fewer communication rounds than baselines and can resist the … Web24 de nov. de 2024 · This repository contains the codes for the paper. On the Convergence of FedAvg on Non-IID Data. Our paper is a tentative theoretical understanding towards …
WebOn the Convergence of FedAvg on Non-IID Data. X. Li, K. Huang, W. Yang, S. Wang, and Z. Zhang. ICLR , OpenReview.net ... search on. Google Scholar Microsoft Bing WorldCat BASE. Tags convergence dblp iclr2024 optimization. Users. Comments and Reviews. This publication has not been reviewed yet. rating distribution. average user rating 0.0 out of ... WebIn this paper, we analyze the convergence of \texttt{FedAvg} on non-iid data and establish a convergence rate of $\mathcal{O}(\frac{1}{T})$ for strongly convex and smooth …
WebOn the Convergence of FedAvg on Non-IID Data - YouTube 0:00 / 13:58 On the Convergence of FedAvg on Non-IID Data 206 views Mar 16, 2024 5 Dislike Share Save …
Web3 de jul. de 2024 · In this paper, we analyze the convergence of \texttt{FedAvg} on non-iid data. We investigate the effect of different sampling and averaging schemes, which are … philips g16.5 ledWebExperimental results demonstrate the effectiveness of FedPNS in accelerating the FL convergence rate, as compared to FedAvg with random node ... 登录/注册. Node Selection Toward Faster Convergence for Federated Learning on Non-IID Data CAS-2 JCR-Q1 SCIE EI Hongda Wu Ping Wang. IEEE Transactions on Network Science and Engineering ... philips g25 soft white light bulbsphilips ga 212 repairWebFedAvg 是经典高效的 FL 算法，但是在现实环境下缺乏理论保障。 本文分析了 FedAvg 在 Non-IID 数据上的收敛性，得到了强凸光滑条件下的收敛率 \mathcal {O} (\frac {1} {T}) ， … philips g3 supportWebIn this paper, we analyze the convergence of \texttt {FedAvg} on non-iid data and establish a convergence rate of O ( 1 T) for strongly convex and smooth problems, … truth in lending act model disclosure formsWebOn the Convergence of FedAvg on Non-IID Data Xiang Li School of Mathematical Sciences Peking University Beijing, 100871, China [email protected] Kaixuan … philips g614 ambiglow spk8614Webprovided new convergence analysis of the well-known federated average (FedAvg) in the non-independent and identically distributed (non-IID) data setting and partial clients … philips g401 keyboard