Exploring the Connection Between Privacy-Preserving ML Techniques and Unlearning

Exploring the challenges and connections between privacy-preserving machine learning techniques like federated learning and homomorphic encryption with the concept of unlearning in machine learning, emphasizing the importance of privacy in unlearning and the limitations of certain techniques in large model training.