no code implementations • 26 Apr 2024 • Duna Zhan, Dongliang Guo, Pengsheng Ji, Sheng Li
FairGI employs the similarity matrix of individuals to achieve individual fairness within groups, while leveraging adversarial learning to address group fairness in terms of both Equal Opportunity and Statistical Parity.
no code implementations • 11 Dec 2023 • Zhongliang Zhou, Mengxuan Hu, Mariah Salcedo, Nathan Gravel, Wayland Yeung, Aarya Venkat, Dongliang Guo, Jielu Zhang, Natarajan Kannan, Sheng Li
Artificial intelligence (AI), particularly machine learning and deep learning models, has significantly impacted bioinformatics research by offering powerful tools for analyzing complex biological data.
no code implementations • 23 Aug 2023 • Ronghang Zhu, Dongliang Guo, Daiqing Qi, Zhixuan Chu, Xiang Yu, Sheng Li
Inspired by the concepts in trustworthy AI, we proposed the first trustworthy representation learning across domains framework which includes four concepts, i. e, robustness, privacy, fairness, and explainability, to give a comprehensive literature review on this research direction.
1 code implementation • 25 Feb 2023 • Dongliang Guo, Zhixuan Chu, Sheng Li
To our best knowledge, FairAC is the first method that jointly addresses the graph attribution completion and graph unfairness problems.
1 code implementation • 13 Feb 2023 • Yizhou Wang, Dongliang Guo, Sheng Li, Octavia Camps, Yun Fu
This paper provides the first survey concentrated on explainable visual anomaly detection methods.