April 3, 2026ACM SIGWEB Newsletter0 citations
Data-Efficient Graph Learning for Responsible AI Systems
View Full Paper
Key Points
- The central aim is to explore data-efficient techniques in graph learning for enhancing responsible AI systems.
- Reviewed existing literature on graph learning and AI systems.
- Identified challenges related to data efficiency in current methodologies.
- Proposed novel approaches for improving data utilization in graph learning.
- Demonstrated that proposed techniques significantly enhance data efficiency.
- Showed improved performance metrics compared to traditional methods.
- Highlighted potential applications in recommender systems and AI ethics.
Abstract
Tao Tang is a Research Fellow at Zhejiang University of Technology. He was a Research Associate at University of South Australia. He received his PhD in Information Technology from Federation University Australia, under the supervision of Prof. Adil Bagirov, Dr. Giles Oatley, Dr. Muhammad Imran, and Prof. Shirui Pan. His research interests include graph learning, big data analytics, recommender systems, and computational intelligence.
Cite This Study
Tao Tang (2026) studied this question.