Code for the paper "DUCK: Distance-based Unlearning via Centroid Kinematics"
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Updated
Apr 13, 2024 - Python
Code for the paper "DUCK: Distance-based Unlearning via Centroid Kinematics"
Unlearning Graph Classifiers with Limited Data Resources (TheWebConf 2023)
An implementation of the SIGMOD24 paper: Machine Unlearning in Learned DBs: An Experimental Analysis
An Empirical Study of Federated Unlearning: Efficiency and Effectiveness (Accepted Conference Track Papers at ACML 2023)
Breaking the Trilemma of Privacy, Utility, Efficiency via Controllable Machine Unlearning
"Challenging Forgets: Unveiling the Worst-Case Forget Sets in Machine Unlearning" by Chongyu Fan*, Jiancheng Liu*, Alfred Hero, Sijia Liu
A framework for machine unlearning.
This repo contains data and code for Task-Aware Machine Unlearning with Application to Load Forecasting.
Code for Large Language Model Unlearning via Embedding-Corrupted Prompts
This repository is an implementation of machine unlearning in deep learning model.
Certified (approximate) machine unlearning for simplified graph convolutional networks (SGCs) with theoretical guarantees (ICLR 2023)
Continual Forgetting for Pre-trained Vision Models (CVPR 2024)
A federated clustering approach with the corresponding unlearning mechanism (ICLR 2023)
Official PyTorch Implementation for Continual Learning and Private Unlearning
Machine Unlearning for Random Forests
Official implementation of "When Machine Unlearning Jeopardizes Privacy" (ACM CCS 2021)
Code for CVPR22 paper "Deep Unlearning via Randomized Conditionally Independent Hessians"
[NeurIPS23 (Spotlight)] "Model Sparsity Can Simplify Machine Unlearning" by Jinghan Jia*, Jiancheng Liu*, Parikshit Ram, Yuguang Yao, Gaowen Liu, Yang Liu, Pranay Sharma, Sijia Liu
General Strategy for Unlearning in Graph Neural Networks
Official implementation of "Graph Unlearning" (ACM CCS 2022)
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