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Machine Unlearning

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Showing 351–375 of 438 papers

TitleStatusHype
Machine Unlearning for Recommendation Systems: An Insight—0
Attack and Reset for Unlearning: Exploiting Adversarial Noise toward Machine Unlearning through Parameter Re-initialization—0
Federated Unlearning for Human Activity Recognition—0
Scissorhands: Scrub Data Influence via Connection Sensitivity in NetworksCode0
Machine unlearning through fine-grained model parameters perturbation—0
eCIL-MU: Embedding based Class Incremental Learning and Machine Unlearning—0
Layer Attack Unlearning: Fast and Accurate Machine Unlearning via Layer Level Attack and Knowledge Distillation—0
Fast-NTK: Parameter-Efficient Unlearning for Large-Scale Models—0
FAST: Feature Aware Similarity Thresholding for Weak Unlearning in Black-Box Generative ModelsCode0
Certified Minimax Unlearning with Generalization Rates and Deletion Capacity—0
Learn to Unlearn for Deep Neural Networks: Minimizing Unlearning Interference with Gradient ProjectionCode0
DUCK: Distance-based Unlearning via Centroid KinematicsCode0
Privacy and Copyright Protection in Generative AI: A Lifecycle Perspective—0
Knowledge Unlearning for LLMs: Tasks, Methods, and Challenges—0
SecureCut: Federated Gradient Boosting Decision Trees with Efficient Machine Unlearning—0
CovarNav: Machine Unlearning via Model Inversion and Covariance Navigation—0
MultiDelete for Multimodal Machine UnlearningCode0
DeepClean: Machine Unlearning on the Cheap by Resetting Privacy Sensitive Weights using the Fisher Diagonal—0
ERASER: Machine Unlearning in MLaaS via an Inference Serving-Aware Approach—0
Breaking the Trilemma of Privacy, Utility, Efficiency via Controllable Machine UnlearningCode0
Open Knowledge Base Canonicalization with Multi-task Unlearning—0
Fast Model Debias with Machine Unlearning—0
Unlearning with Fisher Masking—0
Adapt then Unlearn: Exploiting Parameter Space Semantics for Unlearning in Generative Adversarial Networks—0
FRAMU: Attention-based Machine Unlearning using Federated Reinforcement Learning—0
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