PaperReading20200227

CanChen ggchen@mail.ustc.edu.cn

 
  • Motivation: Current NAS algorithms require lots of computing resources.
  • Method: This paper proposes a novel GCN-based network performance predictor and have done extensive experiments on ImageNet or NAS101.
  • Contribution: This paper is not novel but in my opinion, network performance predictor is the future trend in accelerating NAS.
 

TAPAS

  • Motivation: Current network performance methods do not take dataset difficulty into consideration.
  • Method: The paper proposes a network performance predictor that can adjust to dataset difficulty. Another important thing is that this paper trains the network layer by layer.
  • Contribution: What I learnt is that we can use NN to model a dataset fitting difficulty.
posted @ 2020-02-27 21:14  Klaus-Chen  阅读(97)  评论(0)  编辑  收藏  举报