5 citations · 17 across the 7 of their papers we have counts for
7 papers
Honest Score Client Selection Scheme: Preventing Federated Learning Label Flipping Attacks in Non-IID Scenarios
Yanli Li, Huaming Chen, Wei Bao +2
Federated Learning (FL) is a promising technology that enables multiple actors to build a joint model without sharing their raw data. The distributed nature makes FL vulnerable to…
Handling Heavy Occlusion in Dense Crowd Tracking by Focusing on the Heads
Yu Zhang, Huaming Chen, Wei Bao +3
With the rapid development of deep learning, object detection and tracking play a vital role in today's society. Being able to identify and track all the pedestrians in the dense c…
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…
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…
Random Padding Data Augmentation
Nan Yang, Laicheng Zhong, Fan Huang +2
The convolutional neural network (CNN) learns the same object in different positions in images, which can improve the recognition accuracy of the model. An implication of this is t…
Hierarchical Federated Learning with Momentum Acceleration in Multi-Tier Networks
Zhengjie Yang, Sen Fu, Wei Bao +2
In this paper, we propose Hierarchical Federated Learning with Momentum Acceleration (HierMo), a three-tier worker-edge-cloud federated learning algorithm that applies momentum for…
Fast Multi-label Learning
Xiuwen Gong, Dong Yuan, Wei Bao
Embedding approaches have become one of the most pervasive techniques for multi-label classification. However, the training process of embedding methods usually involves a complex…