237 citations · 723 across the 30 of their papers we have counts for
4 papers · 1 filter
DENSE: Data-Free One-Shot Federated Learning
Jie Zhang, Chen Chen, Bo Li +5
One-shot Federated Learning (FL) has recently emerged as a promising approach, which allows the central server to learn a model in a single communication round. Despite the low com…
A Vertical Federated Learning Framework for Graph Convolutional Network
Xiang Ni, Xiaolong Xu, Lingjuan Lyu +2
Recently, Graph Neural Network (GNN) has achieved remarkable success in various real-world problems on graph data. However in most industries, data exists in the form of isolated i…
DP-SIGNSGD: When Efficiency Meets Privacy and Robustness
Lingjuan Lyu
Federated learning (FL) has emerged as a promising collaboration paradigm by enabling a multitude of parties to construct a joint model without exposing their private training data…
Killing One Bird with Two Stones: Model Extraction and Attribute Inference Attacks against BERT-based APIs
Chen Chen, Xuanli He, Lingjuan Lyu +1
The collection and availability of big data, combined with advances in pre-trained models (e.g., BERT, XLNET, etc), have revolutionized the predictive performance of modern natural…