49 citations · 58 across the 7 of their papers we have counts for
7 papers
Distributed Learning for UAV Swarms
Chen Hu, Hanchi Ren, Jingjing Deng +1
Unmanned Aerial Vehicle (UAV) swarms are increasingly deployed in dynamic, data-rich environments for applications such as environmental monitoring and surveillance. These scenario…
Gradients Stand-in for Defending Deep Leakage in Federated Learning
H. Yi, H. Ren, C. Hu +3
Federated Learning (FL) has become a cornerstone of privacy protection, shifting the paradigm towards localizing sensitive data while only sending model gradients to a central serv…
FissionVAE: Federated Non-IID Image Generation with Latent Space and Decoder Decomposition
Chen Hu, Hanchi Ren, Jingjing Deng +2
Federated learning is a machine learning paradigm that enables decentralized clients to collaboratively learn a shared model while keeping all the training data local. While consid…
Facilitating Feature and Topology Lightweighting: An Ethereum Transaction Graph Compression Method for Malicious Account Detection
Jiajun Zhou, Xuanze Chen, Shengbo Gong +4
Ethereum has become one of the primary global platforms for cryptocurrency, playing an important role in promoting the diversification of the financial ecosystem. However, the rela…
An Element-Wise Weights Aggregation Method for Federated Learning
Yi Hu, Hanchi Ren, Chen Hu +2
Federated learning (FL) is a powerful Machine Learning (ML) paradigm that enables distributed clients to collaboratively learn a shared global model while keeping the data on the o…
A Survey on Vulnerability of Federated Learning: A Learning Algorithm Perspective
Xianghua Xie, Chen Hu, Hanchi Ren +1
This review paper takes a comprehensive look at malicious attacks against FL, categorizing them from new perspectives on attack origins and targets, and providing insights into the…
Toward Data Heterogeneity of Federated Learning
Yuchuan Huang, Chen Hu
Federated learning is a popular paradigm for machine learning. Ideally, federated learning works best when all clients share a similar data distribution. However, it is not always…