Towards Certified Unlearning for Deep Neural Networks
Fuente:
arXiv
Guardado en:
| Autores principales: | Zhang, Binchi, Dong, Yushun, Wang, Tianhao, Li, Jundong |
|---|---|
| Formato: | Preprint |
| Publicado: |
2024
|
| Materias: | |
| Acceso en línea: | |
| Etiquetas: |
Agregar Etiqueta
Sin Etiquetas, Sea el primero en etiquetar este registro!
|
Ejemplares similares
IDEA: A Flexible Framework of Certified Unlearning for Graph Neural Networks
por: Dong, Yushun, et al.
Publicado: (2024)
por: Dong, Yushun, et al.
Publicado: (2024)
Certified Defense on the Fairness of Graph Neural Networks
por: Dong, Yushun, et al.
Publicado: (2023)
por: Dong, Yushun, et al.
Publicado: (2023)
Adversarial Attacks on Fairness of Graph Neural Networks
por: Zhang, Binchi, et al.
Publicado: (2023)
por: Zhang, Binchi, et al.
Publicado: (2023)
Verification of Machine Unlearning is Fragile
por: Zhang, Binchi, et al.
Publicado: (2024)
por: Zhang, Binchi, et al.
Publicado: (2024)
Federated Graph Learning with Graphless Clients
por: Fu, Xingbo, et al.
Publicado: (2024)
por: Fu, Xingbo, et al.
Publicado: (2024)
CREDIT: Certified Ownership Verification of Deep Neural Networks Against Model Extraction Attacks
por: Shen, Bolin, et al.
Publicado: (2026)
por: Shen, Bolin, et al.
Publicado: (2026)
GraphTOP: Graph Topology-Oriented Prompting for Graph Neural Networks
por: Fu, Xingbo, et al.
Publicado: (2025)
por: Fu, Xingbo, et al.
Publicado: (2025)
Graph Neural Networks Are More Than Filters: Revisiting and Benchmarking from A Spectral Perspective
por: Dong, Yushun, et al.
Publicado: (2024)
por: Dong, Yushun, et al.
Publicado: (2024)
Certified Unlearning for Neural Networks
por: Koloskova, Anastasia, et al.
Publicado: (2025)
por: Koloskova, Anastasia, et al.
Publicado: (2025)
Beyond the Permutation Symmetry of Transformers: The Role of Rotation for Model Fusion
por: Zhang, Binchi, et al.
Publicado: (2025)
por: Zhang, Binchi, et al.
Publicado: (2025)
Safety in Graph Machine Learning: Threats and Safeguards
por: Wang, Song, et al.
Publicado: (2024)
por: Wang, Song, et al.
Publicado: (2024)
Towards Quantifying the Hessian Structure of Neural Networks
por: Dong, Zhaorui, et al.
Publicado: (2025)
por: Dong, Zhaorui, et al.
Publicado: (2025)
ST-FiT: Inductive Spatial-Temporal Forecasting with Limited Training Data
por: Lei, Zhenyu, et al.
Publicado: (2024)
por: Lei, Zhenyu, et al.
Publicado: (2024)
PRUNE: A Patching Based Repair Framework for Certifiable Unlearning of Neural Networks
por: Li, Xuran, et al.
Publicado: (2025)
por: Li, Xuran, et al.
Publicado: (2025)
Enhancing Certifiable Semantic Robustness via Robust Pruning of Deep Neural Networks
por: Hu, Hanjiang, et al.
Publicado: (2025)
por: Hu, Hanjiang, et al.
Publicado: (2025)
Federated Graph Learning with Structure Proxy Alignment
por: Fu, Xingbo, et al.
Publicado: (2024)
por: Fu, Xingbo, et al.
Publicado: (2024)
Can Subgraph Explanations Be Weaponized to Steal Graph Neural Networks?
por: Nimase, Ojas, et al.
Publicado: (2026)
por: Nimase, Ojas, et al.
Publicado: (2026)
Exploring and Improving Initialization for Deep Graph Neural Networks: A Signal Propagation Perspective
por: Wang, Senmiao, et al.
Publicado: (2025)
por: Wang, Senmiao, et al.
Publicado: (2025)
Certifying Global Robustness for Deep Neural Networks
por: Li, You, et al.
Publicado: (2024)
por: Li, You, et al.
Publicado: (2024)
CEB: Compositional Evaluation Benchmark for Fairness in Large Language Models
por: Wang, Song, et al.
Publicado: (2024)
por: Wang, Song, et al.
Publicado: (2024)
Fully Decentralized Certified Unlearning
por: Lamri, Hithem, et al.
Publicado: (2025)
por: Lamri, Hithem, et al.
Publicado: (2025)
Certified Signed Graph Unlearning
por: Zhao, Junpeng, et al.
Publicado: (2025)
por: Zhao, Junpeng, et al.
Publicado: (2025)
FairQuant: Certifying and Quantifying Fairness of Deep Neural Networks
por: Kim, Brian Hyeongseok, et al.
Publicado: (2024)
por: Kim, Brian Hyeongseok, et al.
Publicado: (2024)
Harnessing Large Language Models for Disaster Management: A Survey
por: Lei, Zhenyu, et al.
Publicado: (2025)
por: Lei, Zhenyu, et al.
Publicado: (2025)
Virtual Nodes Can Help: Tackling Distribution Shifts in Federated Graph Learning
por: Fu, Xingbo, et al.
Publicado: (2024)
por: Fu, Xingbo, et al.
Publicado: (2024)
Hessian-Free Online Certified Unlearning
por: Qiao, Xinbao, et al.
Publicado: (2024)
por: Qiao, Xinbao, et al.
Publicado: (2024)
Certified Unlearning in Decentralized Federated Learning
por: Wu, Hengliang, et al.
Publicado: (2026)
por: Wu, Hengliang, et al.
Publicado: (2026)
FedHERO: A Federated Learning Approach for Node Classification Task on Heterophilic Graphs
por: Chen, Zihan, et al.
Publicado: (2025)
por: Chen, Zihan, et al.
Publicado: (2025)
Towards a Certified Proof Checker for Deep Neural Network Verification
por: Desmartin, Remi, et al.
Publicado: (2023)
por: Desmartin, Remi, et al.
Publicado: (2023)
Forget by Uncertainty: Orthogonal Entropy Unlearning for Quantized Neural Networks
por: Zhang, Tian, et al.
Publicado: (2026)
por: Zhang, Tian, et al.
Publicado: (2026)
Adaptive Dual Prompting: Hierarchical Debiasing for Fairness-aware Graph Neural Networks
por: Yang, Yuhan, et al.
Publicado: (2025)
por: Yang, Yuhan, et al.
Publicado: (2025)
Edge Prompt Tuning for Graph Neural Networks
por: Fu, Xingbo, et al.
Publicado: (2025)
por: Fu, Xingbo, et al.
Publicado: (2025)
Attack by Unlearning: Unlearning-Induced Adversarial Attacks on Graph Neural Networks
por: Zhang, Jiahao, et al.
Publicado: (2026)
por: Zhang, Jiahao, et al.
Publicado: (2026)
Certified Machine Unlearning via Noisy Stochastic Gradient Descent
por: Chien, Eli, et al.
Publicado: (2024)
por: Chien, Eli, et al.
Publicado: (2024)
MolEdit: Knowledge Editing for Multimodal Molecule Language Models
por: Lei, Zhenyu, et al.
Publicado: (2025)
por: Lei, Zhenyu, et al.
Publicado: (2025)
Rethinking Fair Graph Neural Networks from Re-balancing
por: Li, Zhixun, et al.
Publicado: (2024)
por: Li, Zhixun, et al.
Publicado: (2024)
Forgettable Federated Linear Learning with Certified Data Unlearning
por: Jin, Ruinan, et al.
Publicado: (2023)
por: Jin, Ruinan, et al.
Publicado: (2023)
Rewind-to-Delete: Certified Machine Unlearning for Nonconvex Functions
por: Mu, Siqiao, et al.
Publicado: (2024)
por: Mu, Siqiao, et al.
Publicado: (2024)
Certified Minimax Unlearning with Generalization Rates and Deletion Capacity
por: Liu, Jiaqi, et al.
Publicado: (2023)
por: Liu, Jiaqi, et al.
Publicado: (2023)
How Does Overparameterization Affect Machine Unlearning of Deep Neural Networks?
por: Alon, Gal, et al.
Publicado: (2025)
por: Alon, Gal, et al.
Publicado: (2025)
Ejemplares similares
-
IDEA: A Flexible Framework of Certified Unlearning for Graph Neural Networks
por: Dong, Yushun, et al.
Publicado: (2024) -
Certified Defense on the Fairness of Graph Neural Networks
por: Dong, Yushun, et al.
Publicado: (2023) -
Adversarial Attacks on Fairness of Graph Neural Networks
por: Zhang, Binchi, et al.
Publicado: (2023) -
Verification of Machine Unlearning is Fragile
por: Zhang, Binchi, et al.
Publicado: (2024) -
Federated Graph Learning with Graphless Clients
por: Fu, Xingbo, et al.
Publicado: (2024)