Dynamic regularized sharpness aware minimization in federated learning: Approaching global consistency and smooth landscape

Y Sun, L Shen, S Chen, L Ding… - … Conference on Machine …, 2023 - proceedings.mlr.press
In federated learning (FL), a cluster of local clients are chaired under the coordination of the
global server and cooperatively train one model with privacy protection. Due to the multiple …
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Dynamic Regularized Sharpness Aware Minimization in Federated Learning: Approaching Global Consistency and Smooth Landscape

Y Sun, L Shen, S Chen, L Ding, D Tao - openreview.net
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Dynamic Regularized Sharpness Aware Minimization in Federated Learning: Approaching Global Consistency and Smooth Landscape

Y Sun, L Shen, S Chen, L Ding, D Tao - icml.cc
Dynamic Regularized Sharpness Aware Minimization in Federated Learning: Approaching
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Dynamic Regularized Sharpness Aware Minimization in Federated Learning: Approaching Global Consistency and Smooth Landscape

Y Sun, L Shen, S Chen, L Ding, D Tao - arXiv e-prints, 2023 - ui.adsabs.harvard.edu
In federated learning (FL), a cluster of local clients are chaired under the coordination of the
global server and cooperatively train one model with privacy protection. Due to the multiple …
[PDF] mlr.press

[PDF][PDF] Dynamic Regularized Sharpness Aware Minimization in Federated Learning: Approaching Global Consistency and Smooth Landscape

Y Sun, L Shen, S Chen, L Ding, D Tao - proceedings.mlr.press
In federated learning (FL), a cluster of local clients are chaired under the coordination of the
global server and cooperatively train one model with privacy protection. Due to the multiple …

Dynamic regularized sharpness aware minimization in federated learning: approaching global consistency and smooth landscape

Y Sun, L Shen, S Chen, L Ding, D Tao - Proceedings of the 40th …, 2023 - dl.acm.org
In federated learning (FL), a cluster of local clients are chaired under the coordination of the
global server and cooperatively train one model with privacy protection. Due to the multiple …

Dynamic Regularized Sharpness Aware Minimization in Federated Learning: Approaching Global Consistency and Smooth Landscape

Y Sun, L Shen, S Chen, L Ding, D Tao - arXiv preprint arXiv:2305.11584, 2023 - arxiv.org
In federated learning (FL), a cluster of local clients are chaired under the coordination of the
global server and cooperatively train one model with privacy protection. Due to the multiple …