Demystifying and Mitigating Unfairness for Learning over Graphs

Learn about fairness challenges and mitigation strategies in graph-based machine learning through this IEEE Signal Processing Society webinar presented by UC Irvine's Yanning Shen. Explore key concepts and methodologies for addressing unfairness in graph learning algorithms as part of the Data sciEnce on GrAphS (DEGAS) Webinar Series. Gain insights into how bias can manifest in graph-based systems and discover practical approaches for developing more equitable machine learning models that work with interconnected data structures.