Forgettable Federated Linear Learning with Certified Data Unlearning

Authors: Ruinan Jin, Minghui Chen, Qiong Zhang, Xiaoxiao Li

Published in: IEEE Transactions on Neural Networks and Learning Systems (IEEE TNNLS, 2026), Early Access, pp. 1–10

Earlier workshop version: Forgettable Federated Linear Learning with Certified Data Removal, WWW 2024 FL@FM Workshop (Best Paper Award 🏆)

Overview

Forgettable Federated Linear Learning uses pre-trained models to approximate deep networks linearly during federated training. Its certified unlearning procedure lets the server remove a target client’s contribution without contacting clients again or retaining historical models. Experiments spanning small and large datasets, convolutional networks, and foundation models evaluate the balance between model accuracy and effective unlearning.