• Corpus ID: 54438210

# ProxylessNAS: Direct Neural Architecture Search on Target Task and Hardware

@article{Cai2019ProxylessNASDN,
title={ProxylessNAS: Direct Neural Architecture Search on Target Task and Hardware},
author={Han Cai and Ligeng Zhu and Song Han},
journal={ArXiv},
year={2019},
volume={abs/1812.00332}
}
• Published 27 September 2018
• Computer Science, Mathematics
• ArXiv
Neural architecture search (NAS) has a great impact by automatically designing effective neural network architectures. However, the prohibitive computational demand of conventional NAS algorithms (e.g. $10^4$ GPU hours) makes it difficult to \emph{directly} search the architectures on large-scale tasks (e.g. ImageNet). Differentiable NAS can reduce the cost of GPU hours via a continuous representation of network architecture but suffers from the high GPU memory consumption issue (grow linearly…
969 Citations
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