37 citations · 69 across the 5 of their papers we have counts for
5 papers
Monocular Human-Object Reconstruction in the Wild
Chaofan Huo, Ye Shi, Jingya Wang
Learning the prior knowledge of the 3D human-object spatial relation is crucial for reconstructing human-object interaction from images and understanding how humans interact with o…
FedTP: Federated Learning by Transformer Personalization
Hongxia Li, Zhongyi Cai, Jingya Wang +4
Federated learning is an emerging learning paradigm where multiple clients collaboratively train a machine learning model in a privacy-preserving manner. Personalized federated lea…
Federated Fuzzy Neural Network with Evolutionary Rule Learning
Leijie Zhang, Ye Shi, Yu-Cheng Chang +1
Distributed fuzzy neural networks (DFNNs) have attracted increasing attention recently due to their learning abilities in handling data uncertainties in distributed scenarios. Howe…
Federated Reinforcement Learning for Real-Time Electric Vehicle Charging and Discharging Control
Zixuan Zhang, Yuning Jiang, Yuanming Shi +2
With the recent advances in mobile energy storage technologies, electric vehicles (EVs) have become a crucial part of smart grids. When EVs participate in the demand response progr…
Hierarchical fuzzy neural networks with privacy preservation for heterogeneous big data
Leijie Zhang, Ye Shi, Yu-Cheng Chang +1
Heterogeneous big data poses many challenges in machine learning. Its enormous scale, high dimensionality, and inherent uncertainty make almost every aspect of machine learning dif…