71 citations · 94 across the 5 of their papers we have counts for
5 papers
Federated Learning on Heterogeneous and Long-Tailed Data via Classifier Re-Training with Federated Features
Xinyi Shang, Yang Lu, Gang Huang +1
Federated learning (FL) provides a privacy-preserving solution for distributed machine learning tasks. One challenging problem that severely damages the performance of FL models is…
Demystifying Swarm Learning: A New Paradigm of Blockchain-based Decentralized Federated Learning
Jialiang Han, Yun Ma, Yudong Han
Federated learning (FL) is an emerging promising privacy-preserving machine learning paradigm and has raised more and more attention from researchers and developers. FL keeps users…
Federated Mutual Learning
Tao Shen, Jie Zhang, Xinkang Jia +6
Federated learning (FL) enables collaboratively training deep learning models on decentralized data. However, there are three types of heterogeneities in FL setting bringing about…
Galaxy Learning -- A Position Paper
Chao Wu, Jun Xiao, Gang Huang +1
The recent rapid development of artificial intelligence (AI, mainly driven by machine learning research, especially deep learning) has achieved phenomenal success in various applic…
A Systematic Analysis of Fine-Grained Human Mobility Prediction with On-Device Contextual Data
Huoran Li
User mobility prediction is widely considered to be helpful for various sorts of location based services on mobile devices. A large amount of studies have explored different algori…