409 citations · 670 across the 17 of their papers we have counts for
Showing 2023 · cs.LGShow all
3 papers · 2 filters
cs.LG2023★ 3 cited
FedMAE: Federated Self-Supervised Learning with One-Block Masked Auto-Encoder
Nan Yang, Xuanyu Chen, Charles Z. Liu +3
Latest federated learning (FL) methods started to focus on how to use unlabeled data in clients for training due to users' privacy concerns, high labeling costs, or lack of experti…
cs.LG2023★ 5 cited
FedIL: Federated Incremental Learning from Decentralized Unlabeled Data with Convergence Analysis
Nan Yang, Dong Yuan, Charles Z Liu +2
Most existing federated learning methods assume that clients have fully labeled data to train on, while in reality, it is hard for the clients to get task-specific labels due to us…
cs.LG2023
Federated PCA on Grassmann Manifold for Anomaly Detection in IoT Networks
Tung-Anh Nguyen, Jiayu He, Long Tan Le +2
In the era of Internet of Things (IoT), network-wide anomaly detection is a crucial part of monitoring IoT networks due to the inherent security vulnerabilities of most IoT devices…