34 citations · 53 across the 4 of their papers we have counts for
10 papers
DistFL: Distribution-aware Federated Learning for Mobile Scenarios
Bingyan Liu, Yifeng Cai, Ziqi Zhang +5
Federated learning (FL) has emerged as an effective solution to decentralized and privacy-preserving machine learning for mobile clients. While traditional FL has demonstrated its…
PFA: Privacy-preserving Federated Adaptation for Effective Model Personalization
Bingyan Liu, Yao Guo, Xiangqun Chen
Federated learning (FL) has become a prevalent distributed machine learning paradigm with improved privacy. After learning, the resulting federated model should be further personal…
TransTailor: Pruning the Pre-trained Model for Improved Transfer Learning
Bingyan Liu, Yifeng Cai, Yao Guo +1
The increasing of pre-trained models has significantly facilitated the performance on limited data tasks with transfer learning. However, progress on transfer learning mainly focus…
S3ML: A Secure Serving System for Machine Learning Inference
Junming Ma, Chaofan Yu, Aihui Zhou +6
We present S3ML, a secure serving system for machine learning inference in this paper. S3ML runs machine learning models in Intel SGX enclaves to protect users' privacy. S3ML desig…
Dynamic Slicing for Deep Neural Networks
Ziqi Zhang, Yuanchun Li, Yao Guo +2
Program slicing has been widely applied in a variety of software engineering tasks. However, existing program slicing techniques only deal with traditional programs that are constr…
Adversarial Attacks on Monocular Depth Estimation
Ziqi Zhang, Xinge Zhu, Yingwei Li +2
Recent advances of deep learning have brought exceptional performance on many computer vision tasks such as semantic segmentation and depth estimation. However, the vulnerability o…