Progressive Neural Architecture Search

@inproceedings{Liu2017ProgressiveNA,
  title={Progressive Neural Architecture Search},
  author={Chenxi Liu and Barret Zoph and Jonathon Shlens and Wei Hua and Li-Jia Li and Li Fei-Fei and Alan Loddon Yuille and Jonathan Huang and Kevin P. Murphy},
  booktitle={European Conference on Computer Vision},
  year={2017}
}
We propose a new method for learning the structure of convolutional neural networks (CNNs) that is more efficient than recent state-of-the-art methods based on reinforcement learning and evolutionary algorithms. [] Key Method Our approach uses a sequential model-based optimization (SMBO) strategy, in which we search for structures in order of increasing complexity, while simultaneously learning a surrogate model to guide the search through structure space. Direct comparison under the same search space shows…

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