Machine Unlearning

Machine Unlearning is an emerging data processing technique designed to remove the influence of specific data on a model, thereby achieving privacy protection and compliance management for personal data. Its core objective is to effectively eliminate the impact of designated data points on model parameters without retraining the entire model, ensuring the accuracy and fairness of the model. This technology has significant application value in data privacy protection, model updates, and regulatory compliance, enabling businesses to better manage and maintain their machine learning models.