1 code implementation • 1 May 2023 • Jeffry Wicaksana, Zengqiang Yan, Kwang-Ting Cheng
To overcome this, we propose federated classifier anchoring (FCA) by adding a personalized classifier at each client to guide and debias the federated model through consistency learning.
no code implementations • 9 Jun 2022 • Xijie Huang, Zhiqiang Shen, Shichao Li, Zechun Liu, Xianghong Hu, Jeffry Wicaksana, Eric Xing, Kwang-Ting Cheng
In order to deploy deep models in a computationally efficient manner, model quantization approaches have been frequently used.
1 code implementation • 4 May 2022 • Jeffry Wicaksana, Zengqiang Yan, Dong Zhang, Xijie Huang, Huimin Wu, Xin Yang, Kwang-Ting Cheng
To relax this assumption, in this work, we propose a label-agnostic unified federated learning framework, named FedMix, for medical image segmentation based on mixed image labels.