Ruixuan Li

New methods improve graph learning through non-discrete bandwidth masking techniques.

A new framework to improve learning in Federated Incremental Learning while ensuring data privacy.

pFedDIL improves machine learning by retaining knowledge while adapting to new tasks.

This study examines the reliability of rationalization models under adversarial attacks.

Discover how FedSSI improves machine learning without forgetting past knowledge.

FedGIG tackles privacy risks in graph data training.

Discover how DAMIM improves image understanding in machine learning.