no code implementations • 18 Oct 2023 • Yuhan Yang, Youlong Wu, Yuning Jiang, Yuanming Shi
Distributed learning has become a promising computational parallelism paradigm that enables a wide scope of intelligent applications from the Internet of Things (IoT) to autonomous driving and the healthcare industry.
1 code implementation • 31 Mar 2022 • Yuhan Yang, Yong Zhou, Youlong Wu, Yuanming Shi
Federated learning (FL), as a disruptive machine learning paradigm, enables the collaborative training of a global model over decentralized local datasets without sharing them.
no code implementations • 30 Oct 2020 • Shuhao Xia, Jingyang Zhu, Yuhan Yang, Yong Zhou, Yuanming Shi, Wei Chen
In this paper, we consider federated learning (FL) over a noisy fading multiple access channel (MAC), where an edge server aggregates the local models transmitted by multiple end devices through over-the-air computation (AirComp).
no code implementations • 20 Sep 2018 • Xiaolong Liu, Zhidong Deng, Yuhan Yang
In this paper, we divide semantic image segmentation methods into two categories: traditional and recent DNN method.