PaperReading20200225

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CanChen ggchen@mail.ustc.edu.cn


 

BANANAS

  • Motivation: This paper proposes a network performance predictor to ease the computing pressure in the bayesian optimization process for network architecture search.
  • Method: The paper first uses one-hot path encoding method to represent a network architecure and then trains a accuracy regression model. After that, the author uses the model in the bayesian optimization process and updates it every iteration.
  • Contribution: One-hot path encoding may be important.
 

Best Practices

  • Motivation: NAS has been a hot topic these days but many papers reporting NAS results have some problems.
  • Method: Releasing code in time and making every training detail available are very important.
  • Contribution: Give machine learning researchers a standard guideline for their research.

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