4 papers
FedVeca: Federated Vectorized Averaging on Non-IID Data with Adaptive Bi-directional Global Objective
Ping Luo, Jieren Cheng, Zhenhao Liu +2
Federated Learning (FL) is a distributed machine learning framework to alleviate the data silos, where decentralized clients collaboratively learn a global model without sharing th…
A Secure and Efficient Multi-Object Grasping Detection Approach for Robotic Arms
Hui Wang, Jieren Cheng, Yichen Xu +3
Robotic arms are widely used in automatic industries. However, with wide applications of deep learning in robotic arms, there are new challenges such as the allocation of grasping…
A Novel Optimized Asynchronous Federated Learning Framework
Zhicheng Zhou, Hailong Chen, Kunhua Li +8
Federated Learning (FL) since proposed has been applied in many fields, such as credit assessment, medical, etc. Because of the difference in the network or computing resource, the…
Foreground Object Structure Transfer for Unsupervised Domain Adaptation
Jieren Cheng, Le Liu, Xiangyan Tang +5
Unsupervised domain adaptation aims to train a classification model from the labeled source domain for the unlabeled target domain. Since the data distributions of the two domains…