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How Many Bits Does it Take to Quantize Your Neural Network?EasyChair Preprint 1000, version historyVersion | Date | Pages | Version notes |
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1 | May 25, 2019 | 9 | | 2 | September 12, 2019 | 8 | We provide an example for the non-monotonicity of robustness and improve our experimental evaluation, which now includes a comparison between encodings and against a recently published gradient descent–based method for quantized networks. | 3 | February 24, 2020 | 18 | We provide a comparison between various SMT-solvers. |
Keyphrases: Quantized Neural Networks, SMT solving, adversarial attacks, bit-vectors |
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