Two Papers Accepted by KDD 2026
Our papers “‘Adversarial Signed Graph Learning with Differential Privacy” and “Communication-efficient Federated Graph Classification via Generative Diffusion Modeling” are accepted by SIGKDD Conference on Knowledge Discovery and Data Mining (KDD), 2026. Congratulations to Haobin and Xiuling!