Data-Efficient Graph Learning - Ding, Kaize (Proceedings of the AAAI Conference on Artificial Intelligence, 2024)
My research strives to develop fundamental graph-centric learning algorithms to reduce the need for human supervision in low-resource scenarios. The focus is on achieving effective and reliable data-efficient learning on graphs, which can be summarized into three facets: (1) graph weakly-supervised learning; (2) graph few-shot learning; and (3) graph self-supervised learning.