QVIP: An ILP-based Formal Verification Approach for Quantized Neural Networks. (arXiv:2212.11138v1 [cs.CR])

Deep learning has become a promising programming paradigm in software
development, owing to its surprising performance in solving many challenging
tasks. Deep neural networks (DNNs) are increasingly being deployed in practice,
but are limited on resource-constrained devices owing to their demand for
computational power. Quantization has emerged as a promising technique to
reduce the size of DNNs with comparable accuracy as their floating-point
numbered counterparts. The resulting quantized neural networks (QNNs) can be
implemented energy-efficiently. Similar to their floating-point numbered …

networks neural networks verification