A Sampling Theorem for Exact Identification of Continuous-time Nonlinear Dynamical Systems

no code implementations • 29 Apr 2022 • Zhexuan Zeng, Zuogong Yue, Alexandre Mauroy, Jorge Goncalves, Ye Yuan

The necessary and sufficient condition is proposed -- which is built from Koopman operator -- to the exact identification of the CT system from sampled data.

DeceFL: A Principled Decentralized Federated Learning Framework

1 code implementation • 15 Jul 2021 • Ye Yuan, Jun Liu, Dou Jin, Zuogong Yue, Ruijuan Chen, Maolin Wang, Chuan Sun, Lei Xu, Feng Hua, Xin He, Xinlei Yi, Tao Yang, Hai-Tao Zhang, Shaochun Sui, Han Ding

Although there has been a joint effort in tackling such a critical issue by proposing privacy-preserving machine learning frameworks, such as federated learning, most state-of-the-art frameworks are built still in a centralized way, in which a central client is needed for collecting and distributing model information (instead of data itself) from every other client, leading to high communication pressure and high vulnerability when there exists a failure at or attack on the central client.

Federated Learning Privacy Preserving