8 citations · 14 across the 2 of their papers we have counts for
4 papers
A Secure and Efficient Federated Learning Framework for NLP
Jieren Deng, Chenghong Wang, Xianrui Meng +7
In this work, we consider the problem of designing secure and efficient federated learning (FL) frameworks. Existing solutions either involve a trusted aggregator or require heavyw…
TAG: Gradient Attack on Transformer-based Language Models
Jieren Deng, Yijue Wang, Ji Li +4
Although federated learning has increasingly gained attention in terms of effectively utilizing local devices for data privacy enhancement, recent studies show that publicly shared…
SAPAG: A Self-Adaptive Privacy Attack From Gradients
Yijue Wang, Jieren Deng, Dan Guo +5
Distributed learning such as federated learning or collaborative learning enables model training on decentralized data from users and only collects local gradients, where data is p…
ESMFL: Efficient and Secure Models for Federated Learning
Sheng Lin, Chenghong Wang, Hongjia Li +3
Nowadays, Deep Neural Networks are widely applied to various domains. However, massive data collection required for deep neural network reveals the potential privacy issues and als…