“Neural Architecture Search With Reinforcement Learning”(2017) 논문.pdf

1611.01578.pdf
Preview of “Neural Architecture Search with reinforcement learning”(2017) 논문
🔗 Source: arxiv.org
📊 Size: 716 KB
📄 Pages: 16 pages
⬇️ Downloads: 99

Summary

Neural Architecture Search uses a recurrent network to generate model descriptions of neural networks and trains this RNN with reinforcement learning to maximize the expected accuracy of the generated architectures. The method can design novel network architectures that rival the best human-invented architectures, achieving a test error rate of 3.65 on CIFAR-10 and a test set perplexity of 62.4 on Penn Treebank.

Description

Neural Architecture Search uses a recurrent network to generate model descriptions of neural networks and trains this RNN with reinforcement learning to...

Technical Information

  • File Format: PDF
  • File Size: 716 KB
  • Pages: 16
  • Language: EN
  • Total Downloads: 99
  • Last Updated: 1 month ago

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