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

Han CaiLigeng ZhuSong Han

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)... (read more)

PDF Abstract

1,157
 ↳ Quickstart in
972
See all 9 implementations