LymphNode enforces default-deny access control on DNNs by injecting GSUAP into the feature space to neutralize utility for unauthorized queries and selectively restore it for authorized inputs carrying a stealthy credential, using under 100 samples from surrogate data.
Reading digits in natural images with unsupervised feature learning
3 Pith papers cite this work. Polarity classification is still indexing.
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Fed-BAC uses contextual bandits and Thompson Sampling with additive clustering to deliver up to 35.5 percentage point accuracy gains and 1.5-4.8x faster convergence in hierarchical federated learning on non-IID data.
Threshold Modulation dynamically adjusts firing thresholds in SNNs via neuronal dynamics-inspired normalization to enable online test-time adaptation under distribution shifts.
citing papers explorer
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LymphNode: A Plug-and-Play Access Control Method for Deep Neural Networks
LymphNode enforces default-deny access control on DNNs by injecting GSUAP into the feature space to neutralize utility for unauthorized queries and selectively restore it for authorized inputs carrying a stealthy credential, using under 100 samples from surrogate data.
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Fed-BAC: Federated Bandit-Guided Additive Clustering in Hierarchical Federated Learning
Fed-BAC uses contextual bandits and Thompson Sampling with additive clustering to deliver up to 35.5 percentage point accuracy gains and 1.5-4.8x faster convergence in hierarchical federated learning on non-IID data.
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Threshold Modulation for Online Test-Time Adaptation of Spiking Neural Networks
Threshold Modulation dynamically adjusts firing thresholds in SNNs via neuronal dynamics-inspired normalization to enable online test-time adaptation under distribution shifts.