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Efficient Vertical Federated Unlearning via Fast Retraining
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What this work says
Outgoing claims: the papers this work cites, builds on, or argues with.
inferredcites →https://doi.org/10.1007/978-3-319-57959-7openalex-snapshot
The EU General Data Protection Regulation (GDPR)
inferredcites →https://doi.org/10.1109/5.726791openalex-snapshot
Gradient-based learning applied to document recognition
inferredcites →https://doi.org/10.1109/cvpr.2009.5206848openalex-snapshot
ImageNet: A large-scale hierarchical image database
inferredcites →https://doi.org/10.1109/cvpr.2015.7298801openalex-snapshot
3D ShapeNets: A deep representation for volumetric shapes
inferredcites →https://doi.org/10.1109/cvpr.2016.90openalex-snapshot
Deep Residual Learning for Image Recognition
inferredcites →https://doi.org/10.1109/cvpr.2019.00985openalex-snapshot
PointConv: Deep Convolutional Networks on 3D Point Clouds
inferredcites →https://doi.org/10.1109/cvprw56347.2022.00482openalex-snapshot
Efficient Two-stage Model Retraining for Machine Unlearning
inferredcites →https://doi.org/10.1109/icassp.2017.7952190openalex-snapshot
Very deep convolutional neural networks for raw waveforms
inferredcites →https://doi.org/10.1109/infocom48880.2022.9796721openalex-snapshot
The Right to be Forgotten in Federated Learning: An Efficient Realization with Rapid Retraining
inferredcites →https://doi.org/10.1109/iwqos52092.2021.9521274openalex-snapshot
FedEraser: Enabling Efficient Client-Level Data Removal from Federated Learning Models
inferredcites →https://doi.org/10.1109/msp.2020.2975749openalex-snapshot
Federated Learning: Challenges, Methods, and Future Directions
inferredcites →https://doi.org/10.1109/tbdata.2022.3192121openalex-snapshot
Defending Batch-Level Label Inference and Replacement Attacks in Vertical Federated Learning
inferredcites →https://doi.org/10.1109/tdsc.2022.3208630openalex-snapshot
Your Labels are Selling You Out: Relation Leaks in Vertical Federated Learning
inferredcites →https://doi.org/10.1109/tdsc.2024.3382321openalex-snapshot
VeriFi: Towards Verifiable Federated Unlearning
inferredcites →https://doi.org/10.1109/tkde.2024.3352628openalex-snapshot
Vertical Federated Learning: Concepts, Advances, and Challenges
inferredcites →https://doi.org/10.1109/tpds.2020.3023905openalex-snapshot
Towards Efficient Scheduling of Federated Mobile Devices Under Computational and Statistical Heterogeneity
inferredcites →https://doi.org/10.1109/trustcom50675.2020.00098openalex-snapshot
Multi-party Private Set Intersection in Vertical Federated Learning
inferredcites →https://doi.org/10.1109/tsp.2022.3198176openalex-snapshot
FedBCD: A Communication-Efficient Collaborative Learning Framework for Distributed Features
inferredcites →https://doi.org/10.1145/3485447.3512222openalex-snapshot
Federated Unlearning via Class-Discriminative Pruning
inferredcites →https://doi.org/10.24963/ijcai.2022/553openalex-snapshot
Learnability of Competitive Threshold Models
inferredcites →https://doi.org/10.3390/a15040104openalex-snapshot
Federated Learning for Intrusion Detection in the Critical Infrastructures: Vertically Partitioned Data Use Case
inferredcites →https://doi.org/10.48550/arxiv.1212.5701openalex-snapshot
ADADELTA: An Adaptive Learning Rate Method
inferredcites →https://doi.org/10.48550/arxiv.1609.04747openalex-snapshot
An overview of gradient descent optimization algorithms
inferredcites →https://doi.org/10.48550/arxiv.1712.07628openalex-snapshot
Improving Generalization Performance by Switching from Adam to SGD
inferredcites →https://doi.org/10.48550/arxiv.1804.03209openalex-snapshot
Google Speech Commands-Musan test set
inferredcites →https://doi.org/10.48550/arxiv.1812.00564openalex-snapshot
Split learning for health: Distributed deep learning without sharing raw patient data
inferredcites →https://doi.org/10.48550/arxiv.2004.07427openalex-snapshot
Asymmetrical Vertical Federated Learning
inferredcites →https://doi.org/10.48550/arxiv.2103.11870openalex-snapshot
A Federated Learning Framework for Smart Grids: Securing Power Traces in Collaborative Learning
inferredcites →https://doi.org/10.48550/arxiv.2104.00489openalex-snapshot
PyVertical: A Vertical Federated Learning Framework for Multi-headed SplitNN
inferredcites →https://doi.org/10.48550/arxiv.2110.15122openalex-snapshot
CAFE: Catastrophic Data Leakage in Vertical Federated Learning
inferredcites →https://doi.org/10.48550/arxiv.2201.09441openalex-snapshot
Federated Unlearning with Knowledge Distillation
inferredcites →https://doi.org/10.48550/arxiv.2202.04309openalex-snapshot
Vertical Federated Learning: Challenges, Methodologies and Experiments
inferredcites →https://doi.org/10.5555/1953048.2021068openalex-snapshot
Adaptive Subgradient Methods for Online Learning and Stochastic Optimization
inferredcites →https://doi.org/10.69554/tcfn5165openalex-snapshot
Understanding the scope and impact of the California Consumer Privacy Act of 2018
What points at this work
Incoming claims: where this work appears in other papers’ reference lists and arguments.
inferred← citeshttps://doi.org/10.1007/978-981-95-3001-4_1openalex-snapshot
Label Inference Attacks Against Federated Unlearning
inferred← citeshttps://doi.org/10.1016/j.future.2026.108669openalex-snapshot
DistillVFL: A Knowledge Distillation-enhanced Vertical Federated Learning framework for scalable cross-silo collaboration
inferred← citeshttps://doi.org/10.1109/access.2025.3600884openalex-snapshot
A Survey of Challenges and Opportunities in Vertical Federated Unlearning
inferred← citeshttps://doi.org/10.1109/bigdata66926.2025.11401076openalex-snapshot
Vertical Federated Learning on Scattered Directive: Enforcing Policies on VFL Workflows
inferred← citeshttps://doi.org/10.1109/ijcnn64981.2025.11228643openalex-snapshot
Federated Unlearning with Oriented Saliency Compression
inferred← citeshttps://doi.org/10.1109/tdsc.2024.3520614openalex-snapshot
FedU: Federated Unlearning via User-Side Influence Approximation Forgetting
inferred← citeshttps://doi.org/10.1109/tdsc.2025.3630811openalex-snapshot
Hidden Threats in Federated Unlearning: Camouflaged Poisoning Attacks and Their Unlearning Consequences
inferred← citeshttps://doi.org/10.1109/tifs.2026.3734781openalex-snapshot
Practical Federated Unlearning: A Target Client-Driven Approach to Model Forgetting
inferred← citeshttps://doi.org/10.1109/tkde.2025.3613659openalex-snapshot
FELEMN: Toward Efficient Feature-Level Machine Unlearning for Exact Privacy Protection
inferred← citeshttps://doi.org/10.1109/tnse.2025.3637602openalex-snapshot
LVFUS: Vertical Federated Unlearning for Intelligent Network Security via Adaptive Optimizer Switching
inferred← citeshttps://doi.org/10.1111/exsy.70063openalex-snapshot
SoK : Federated Learning and Unlearning for Medical Image Analysis
inferred← citeshttps://doi.org/10.1145/3679014openalex-snapshot
A Survey on Federated Unlearning: Challenges, Methods, and Future Directions
inferred← citeshttps://doi.org/10.1145/3746252.3761091openalex-snapshot
EFU: Enforcing Federated Unlearning via Functional Encryption
inferred← citeshttps://doi.org/10.23919/indiacom70271.2026.11526695openalex-snapshot
A Novel Algorithm on Analysis of a Contextual Machine Learning System for Task Offloading for Efficient Mobile Cloud Processing
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