30 citations · 37 across the 6 of their papers we have counts for
6 papers
Federated Learning with Privacy-Preserving Ensemble Attention Distillation
Xuan Gong, Liangchen Song, Rishi Vedula +8
Federated Learning (FL) is a machine learning paradigm where many local nodes collaboratively train a central model while keeping the training data decentralized. This is particula…
Preserving Privacy in Federated Learning with Ensemble Cross-Domain Knowledge Distillation
Xuan Gong, Abhishek Sharma, Srikrishna Karanam +4
Federated Learning (FL) is a machine learning paradigm where local nodes collaboratively train a central model while the training data remains decentralized. Existing FL methods ty…
Self-supervised Human Mesh Recovery with Cross-Representation Alignment
Xuan Gong, Meng Zheng, Benjamin Planche +4
Fully supervised human mesh recovery methods are data-hungry and have poor generalizability due to the limited availability and diversity of 3D-annotated benchmark datasets. Recent…
Deformable Gabor Feature Networks for Biomedical Image Classification
Xuan Gong, Xin Xia, Wentao Zhu +3
In recent years, deep learning has dominated progress in the field of medical image analysis. We find however, that the ability of current deep learning approaches to represent the…
A Review of Recent Advances of Binary Neural Networks for Edge Computing
Wenyu Zhao, Teli Ma, Xuan Gong +2
Edge computing is promising to become one of the next hottest topics in artificial intelligence because it benefits various evolving domains such as real-time unmanned aerial syste…
Anti-Bandit Neural Architecture Search for Model Defense
Hanlin Chen, Baochang Zhang, Song Xue +4
Deep convolutional neural networks (DCNNs) have dominated as the best performers in machine learning, but can be challenged by adversarial attacks. In this paper, we defend against…