183 citations · 251 across the 7 of their papers we have counts for
10 papers
Differential Advising in Multi-Agent Reinforcement Learning
Dayong Ye, Tianqing Zhu, Zishuo Cheng +2
Agent advising is one of the main approaches to improve agent learning performance by enabling agents to share advice. Existing advising methods have a common limitation that an ad…
From Distributed Machine Learning To Federated Learning: In The View Of Data Privacy And Security
Sheng Shen, Tianqing Zhu, Di Wu +2
Federated learning is an improved version of distributed machine learning that further offloads operations which would usually be performed by a central server. The server becomes…
Correlated Differential Privacy: Feature Selection in Machine Learning
Tao Zhang, Tianqing Zhu, Ping Xiong +3
Privacy preserving in machine learning is a crucial issue in industry informatics since data used for training in industries usually contain sensitive information. Existing differe…
Fairness in Semi-supervised Learning: Unlabeled Data Help to Reduce Discrimination
Tao Zhang, Tianqing Zhu, Jing Li +3
A growing specter in the rise of machine learning is whether the decisions made by machine learning models are fair. While research is already underway to formalize a machine-learn…
Fairness Constraints in Semi-supervised Learning
Tao Zhang, Tianqing Zhu, Mengde Han +3
Fairness in machine learning has received considerable attention. However, most studies on fair learning focus on either supervised learning or unsupervised learning. Very few cons…
A Differentially Private Game Theoretic Approach for Deceiving Cyber Adversaries
Dayong Ye, Tianqing Zhu, Shen Sheng +1
Cyber deception is one of the key approaches used to mislead attackers by hiding or providing inaccurate system information. There are two main factors limiting the real-world appl…