no code implementations • 26 Mar 2024 • Shijie Na, Yuzhi Liang, Siu-Ming Yiu
Federated learning client selection is crucial for determining participant clients while balancing model accuracy and communication efficiency.
no code implementations • 25 Jul 2023 • Junbin Fang, Canjian Jiang, You Jiang, Puxi Lin, Zhaojie Chen, Yujing Sun, Siu-Ming Yiu, Zoe L. Jiang
Although face recognition starts to play an important role in our daily life, we need to pay attention that data-driven face recognition vision systems are vulnerable to adversarial attacks.
no code implementations • 22 Mar 2023 • Junbin Fang, You Jiang, Canjian Jiang, Zoe L. Jiang, Siu-Ming Yiu, Chuanyi Liu
This paper focuses on optical-based physical adversarial attack techniques for computer vision systems, with emphasis on the introduction and discussion of optical-based physical adversarial attack techniques.
no code implementations • 17 Nov 2022 • Hongxiao Wang, Zoe L. Jiang, Yanmin Zhao, Siu-Ming Yiu, Peng Yang, Man Chen, Zejiu Tan, Bohan Jin
Therefore, it is still hard to perform common machine learning such as logistic regression and neural networks in high performance.
1 code implementation • 12 Nov 2022 • Qianru Zhang, Zheng Wang, Cheng Long, Chao Huang, Siu-Ming Yiu, Yiding Liu, Gao Cong, Jieming Shi
Detecting anomalous trajectories has become an important task in many location-based applications.
no code implementations • 12 May 2022 • Zoe L. Jiang, Jiajing Gu, Hongxiao Wang, Yulin Wu, Junbin Fang, Siu-Ming Yiu, Wenjian Luo, Xuan Wang
So machine learning tasks need to be spread across multiple servers, turning the centralized machine learning into a distributed one.