Awesome Machine Unlearning (A Survey of Machine Unlearning)

Awesome Federated Unlearning (FU) Papers (Continually Update)

An Empirical Study of Federated Unlearning: Efficiency and Effectiveness (Accepted Conference Track Papers at ACML 2023)

This repository contains the proposed Federated Feature Unlearning framework, which introduces feature-level unlearning in federated environments by utilizing local feature sensitivity.

Papers related to Machine/ Federated Unlearning in all top venues

This repository contains the artifacts for FULDebug, a federated unlearning debugging framework developed as part of our research.