GENIU: A Restricted Data Access Unlearning for Imbalanced Data

Understand

With the increasing emphasis on data privacy, the significance of machine unlearning has grown substantially.

• Class unlearning, which involves enabling a trained model to forget data belonging to a specific class learned before, is important as classification tasks account for the majority of today's machine learning as a service (MLaaS).
• Retraining the model on the original data, excluding the data to be forgotten (a.k.a forgetting data), is a common approach to class unlearning.
• However, the availability of original data during the unlearning phase is not always guaranteed, leading to the exploration of class unlearning with restricted data access.