2025
DynFrs: An Efficient Framework for Machine Unlearning in Random Forest
ICLR 2025poster
Random Forests are widely recognized for establishing efficacy in classification and regression tasks, standing out in various domains such as medical diagnosis, finance, and personalized recommendations. These domains, however, are inherently sensitive to privacy concerns, as personal and confident…