• Corpus ID: 240354214

# Beta-CROWN: Efficient Bound Propagation with Per-neuron Split Constraints for Complete and Incomplete Neural Network Robustness Verification

@inproceedings{Wang2021BetaCROWNEB,
title={Beta-CROWN: Efficient Bound Propagation with Per-neuron Split Constraints for Complete and Incomplete Neural Network Robustness Verification},
author={Shiqi Wang and Huan Zhang and Kaidi Xu and Xue Lin and Suman Sekhar Jana and Cho-Jui Hsieh and J. Zico Kolter},
year={2021}
}
• Published 11 March 2021
• Computer Science
Bound propagation based incomplete neural network verifiers such as CROWN are very efficient and can significantly accelerate branch-and-bound (BaB) based complete verification of neural networks. However, bound propagation cannot fully handle the neuron split constraints introduced by BaB commonly handled by expensive linear programming (LP) solvers, leading to loose bounds and hurting verification efficiency. In this work, we develop β-CROWN, a new bound propagation based method that can…
1 Citations

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