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"
An implementation of the SIGMOD24 paper: Machine Unlearning in Learned DBs: An Experimental Analysis
Unlearning Graph Classifiers with Limited Data Resources (TheWebConf 2023)
USENIX Security'23: Inductive Graph Unlearning
A curated list of Machine Unlearning, focusing on deep learning applications.
This project explores the efficacy of machine unlearning methods like Task-Agnostic Machine Unlearning and SISA in enhancing privacy and reducing bias in facial recognition systems, emphasizing their importance in responsible technology implementation.
An Empirical Study of Federated Unlearning: Efficiency and Effectiveness (Accepted Conference Track Papers at ACML 2023)
"Challenging Forgets: Unveiling the Worst-Case Forget Sets in Machine Unlearning" by Chongyu Fan*, Jiancheng Liu*, Alfred Hero, Sijia Liu
Breaking the Trilemma of Privacy, Utility, Efficiency via Controllable Machine Unlearning
Continual Forgetting for Pre-trained Vision Models (CVPR 2024)
A framework for machine unlearning.
This repo contains data and code for Task-Aware Machine Unlearning with Application to Load Forecasting.
A resource repository for machine unlearning in large language models
# kaefa kwangwoon automated exploratory factor analysis for improving research capability to identify unexplained factor structure with complexly cross-classified multilevel structured data in R environment
Official Website of https://github.com/tamlhp/awesome-machine-unlearning
Certified (approximate) machine unlearning for simplified graph convolutional networks (SGCs) with theoretical guarantees (ICLR 2023)
Official PyTorch Implementation for Continual Learning and Private Unlearning
A federated clustering approach with the corresponding unlearning mechanism (ICLR 2023)
A notebook of awesome privacy protection,federated learning, fairness and blockchain research materials.
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