Regularized Evolution for Image Classifier Architecture Search

@inproceedings{Real2019RegularizedEF,
  title={Regularized Evolution for Image Classifier Architecture Search},
  author={E. Real and A. Aggarwal and Y. Huang and Quoc V. Le},
  booktitle={AAAI},
  year={2019}
}
The effort devoted to hand-crafting image classifiers has motivated the use of architecture search to discover them automatically. [...] Key Result These models set a new state of the art for CIFAR-10 (mean test error = 2.13%) and mobile-size ImageNet (top-5 accuracy = 92.1% with 5.06M parameters), and reach the current state of the art for ImageNet (top-5 accuracy = 96.2%).Expand
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