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We propose Stochastic Neural Architecture Search (SNAS), an economical end-to-end solution to Neural Architecture Search (NAS) that trains neural operation parameters and architecture distribution parameters in same round of back-propagation, while maintaining the completeness and differentiability of the NAS pipeline.
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Shufflenet: An extremely efficient convolutional neural network for mobile devices. arxiv 2017
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Barret Zoph, Vijay Vasudevan, Jonathon Shlens, and Quoc V Le · 2017
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