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Machine Unlearning

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Showing 301–350 of 438 papers

TitleStatusHype
Example-based Explanations for Random Forests using Machine Unlearning—0
Separable Multi-Concept Erasure from Diffusion Models—0
An Information Theoretic Approach to Machine UnlearningCode1
Unlearnable Algorithms for In-context Learning—0
Machine Unlearning for Image-to-Image Generative ModelsCode1
Dataset Condensation Driven Machine UnlearningCode0
CaMU: Disentangling Causal Effects in Deep Model UnlearningCode0
Towards Effective and General Graph Unlearning via Mutual EvolutionCode0
Contrastive Unlearning: A Contrastive Approach to Machine Unlearning—0
Langevin Unlearning: A New Perspective of Noisy Gradient Descent for Machine UnlearningCode0
Federated Unlearning for Human Activity Recognition—0
Machine Unlearning for Recommendation Systems: An Insight—0
Attack and Reset for Unlearning: Exploiting Adversarial Noise toward Machine Unlearning through Parameter Re-initialization—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
Reinforcement UnlearningCode1
FAST: Feature Aware Similarity Thresholding for Weak Unlearning in Black-Box Generative ModelsCode0
Fast-NTK: Parameter-Efficient Unlearning for Large-Scale Models—0
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
Deep Unlearning: Fast and Efficient Gradient-free Approach to Class ForgettingCode1
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
Towards Machine Unlearning Benchmarks: Forgetting the Personal Identities in Facial Recognition SystemsCode1
Breaking the Trilemma of Privacy, Utility, Efficiency via Controllable Machine UnlearningCode0
Detecting Pretraining Data from Large Language ModelsCode2
Open Knowledge Base Canonicalization with Multi-task Unlearning—0
SalUn: Empowering Machine Unlearning via Gradient-based Weight Saliency in Both Image Classification and GenerationCode1
Fast Model Debias with Machine Unlearning—0
In-Context Unlearning: Language Models as Few Shot UnlearnersCode1
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
Exploiting Machine Unlearning for Backdoor Attacks in Deep Learning System—0
Tight Bounds for Machine Unlearning via Differential Privacy—0
Task-Aware Machine Unlearning and Its Application in Load ForecastingCode1
Machine Unlearning Methodology base on Stochastic Teacher Network—0
Heterogeneous Decentralized Machine Unlearning with Seed Model Distillation—0
Machine Unlearning for Causal Inference—0
Generative Adversarial Networks Unlearning—0
Fast Machine Unlearning Without Retraining Through Selective Synaptic DampeningCode1
Machine Unlearning: Solutions and ChallengesCode2
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