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Found 3 papers, 1 papers with code
AutoReCon: Neural Architecture Search-based Reconstruction for Data-free Compression
Thus, a common approach is to compute a reconstructed training dataset before compression.
NASB: Neural Architecture Search for Binary Convolutional Neural Networks
In this paper, we propose a strategy, named NASB, which adopts Neural Architecture Search (NAS) to find an optimal architecture for the binarization of CNNs.
Towards Lossless Binary Convolutional Neural Networks Using Piecewise Approximation
Binary Convolutional Neural Networks (CNNs) can significantly reduce the number of arithmetic operations and the size of memory storage, which makes the deployment of CNNs on mobile or embedded systems more promising.
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