8 citations · 9 across the 2 of their papers we have counts for
5 papers
A New Distributed Method for Training Generative Adversarial Networks
Jinke Ren, Chonghe Liu, Guanding Yu +1
Generative adversarial networks (GANs) are emerging machine learning models for generating synthesized data similar to real data by jointly training a generator and a discriminator…
Scheduling for Cellular Federated Edge Learning with Importance and Channel Awareness
Jinke Ren, Yinghui He, Dingzhu Wen +3
In cellular federated edge learning (FEEL), multiple edge devices holding local data jointly train a neural network by communicating learning updates with an access point without e…
An Overview of Data-Importance Aware Radio Resource Management for Edge Machine Learning
Dingzhu Wen, Xiaoyang Li, Qunsong Zeng +2
The 5G network connecting billions of Internet-of-Things (IoT) devices will make it possible to harvest an enormous amount of real-time mobile data. Furthermore, the 5G virtualizat…
Accelerating DNN Training in Wireless Federated Edge Learning Systems
Jinke Ren, Guanding Yu, Guangyao Ding
Training task in classical machine learning models, such as deep neural networks, is generally implemented at a remote cloud center for centralized learning, which is typically tim…
An Edge-Computing Based Architecture for Mobile Augmented Reality
Jinke Ren, Yinghui He, Guan Huang +3
In order to mitigate the long processing delay and high energy consumption of mobile augmented reality (AR) applications, mobile edge computing (MEC) has been recently proposed and…