Fine-Grained Neural Architecture Search

18 Nov 2019Heewon KimSeokil HongBohyung HanHeesoo MyeongKyoung Mu Lee

We present an elegant framework of fine-grained neural architecture search (FGNAS), which allows to employ multiple heterogeneous operations within a single layer and can even generate compositional feature maps using several different base operations. FGNAS runs efficiently in spite of significantly large search space compared to other methods because it trains networks end-to-end by a stochastic gradient descent method... (read more)

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