no code implementations • NeurIPS 2021 • Shangshu Qian, Hung Pham, Thibaud Lutellier, Zeou Hu, Jungwon Kim, Lin Tan, YaoLiang Yu, Jiahao Chen, Sameena Shah
Our study of 22 mitigation techniques and five baselines reveals up to 12. 6% fairness variance across identical training runs with identical seeds.
no code implementations • 12 Aug 2021 • Saber Malekmohammadi, Kiarash Shaloudegi, Zeou Hu, YaoLiang Yu
Over the past few years, the federated learning ($\texttt{FL}$) community has witnessed a proliferation of new $\texttt{FL}$ algorithms.
1 code implementation • 20 Jun 2020 • Zeou Hu, Kiarash Shaloudegi, Guojun Zhang, Yao-Liang Yu
Federated learning has emerged as a promising, massively distributed way to train a joint deep model over large amounts of edge devices while keeping private user data strictly on device.