Machine learning has achieved remarkable success in many applications. However,
existing studies are largely based on the closed-world assumption, which assumes that the …

Medical imaging analysis has witnessed remarkable advancements even surpassing
human-level performance in recent years, driven by the rapid development of advanced …

Existing federated learning methods have effectively dealt with decentralized learning in
scenarios involving data privacy and non-IID data. However, in real-world situations, each …

Existing federated learning methods have effectively addressed decentralized learning in
scenarios involving data privacy and non-IID data. However, in real-world situations, each …

Continual learning aims to equip models with the ability to retain previously learned
knowledge like a human. Recent work incorporating Parameter-Efficient Fine-Tuning has …

Technological advances in deep learning have brought remarkable performance in the
object classification task but only when all the training data of classes to be learned are …

This thesis explores how to make AI systems learn and adapt on their own in a changing
world. It develops new methods to help AI recognize unknown data, group it into meaningful …