PAC-guaranteed framework for counting inputs satisfying logical properties in neural networks, instantiated as NPAQ for binarized networks and applied to robustness, trojan efficacy, and bias analyses.
Taming the Curse of Dimensionality: Discrete Integration by Hashing and Optimization
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Quantitative Verification of Neural Networks And its Security Applications
PAC-guaranteed framework for counting inputs satisfying logical properties in neural networks, instantiated as NPAQ for binarized networks and applied to robustness, trojan efficacy, and bias analyses.