As privacy concerns escalate in the realm of machine learning, data owners now have the
option to utilize machine unlearning to remove their data from machine learning models …

Pre-trained Large Language Models (LLMs) have demonstrated remarkable capabilities but
also pose risks by learning and generating copyrighted material, leading to significant legal …

In light of recent privacy regulations, machine unlearning has attracted significant attention
in the research community. However, current studies predominantly assess the overall …

The increasing integration of artificial intelligence (AI) in healthcare holds great promise for
enhancing patient care through predictive modeling and clinical decision support. However …

Machine unlearning algorithms aim to efficiently remove data from a model without
retraining it from scratch, in order to enforce data privacy, remove corrupted or outdated …

Machine unlearning aims to eliminate the influence of a subset of training samples (ie,
unlearning samples) from a trained model. Effectively and efficiently removing the …