1 code implementation • 22 Oct 2021 • Bingyan Liu, Yifeng Cai, Ziqi Zhang, Yuanchun Li, Leye Wang, Ding Li, Yao Guo, Xiangqun Chen
Previous studies focus on the "symptoms" directly, as they try to improve the accuracy or detect possible attacks by adding extra steps to conventional FL models.
1 code implementation • 2 Mar 2021 • Bingyan Liu, Yao Guo, Xiangqun Chen
Based on the grouping results, PFA conducts an FL process in a group-wise way on the federated model to accomplish the adaptation.
no code implementations • 2 Mar 2021 • Bingyan Liu, Yifeng Cai, Yao Guo, Xiangqun Chen
This paper aims to improve the transfer performance from another angle - in addition to tuning the weights, we tune the structure of pre-trained models, in order to better match the target task.
no code implementations • 13 Oct 2020 • Junming Ma, Chaofan Yu, Aihui Zhou, Bingzhe Wu, Xibin Wu, Xingyu Chen, Xiangqun Chen, Lei Wang, Donggang Cao
We present S3ML, a secure serving system for machine learning inference in this paper.
no code implementations • 23 Mar 2020 • Ziqi Zhang, Xinge Zhu, Yingwei Li, Xiangqun Chen, Yao Guo
In order to understand the impact of adversarial attacks on depth estimation, we first define a taxonomy of different attack scenarios for depth estimation, including non-targeted attacks, targeted attacks and universal attacks.
no code implementations • 29 Nov 2018 • Lijun Yu, Dawei Zhang, Xiangqun Chen, Alexander Hauptmann
Therefore, we developed a model to predict and identify car crashes from surveillance cameras based on a 3D reconstruction of the road plane and prediction of trajectories.
no code implementations • 22 Jul 2018 • Lijun Yu, Dawei Zhang, Xiangqun Chen, Xing Xie
In this paper, we introduce MOBA-Slice, a time slice based evaluation framework of relative advantage between teams in MOBA games.