CanChen ggchen@mail.ustc.edu.cn

 

To share or not share

  • Motivation: With the publiaction of NAS101, the author wants to study how weight sharing work in different search spaces and the correlation between the supernet and results returned by NAS101.
  • Method: The paper did extensive experiments in weight sharing methods with different search spaces and showed that search space plays an important role in the correlation.
  • Contribution: The work made good use of NAS101 but I did not see any novelty in this work.
 

NAS EVALUATION IS FRUSTRATINGLY HARD

  • Motivation: NAS needs some criteria.
  • Method: This paper did a wide range of experiments and showed that cell-based searched models tends to have similar accuracies.
    Also, the selection of seeds and macro structures are important. The operations, instead, have less impact on the performance.
  • Contribution: This paper is a ILCR paper, probably because this paper analysed some important issues in NAS evaluation.

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