RE (Real et al., 2019)

Reported on 6 benchmarks across 2 tasks · 1 paper · 2 SOTA

Note: results are matched by exact model name. Different papers may use the same name for different model variants.

Methodology6 results

Neural Architecture SearchonNATS-Bench Topology, CIFAR-10
Test Accuracy· 2018-02-05
94.13
SOTA
Regularized Evolution for Image Classifier Architecture Search arXiv:1802.01548
AutoMLonNATS-Bench Topology, CIFAR-10
Test Accuracy· 2018-02-05
94.13
SOTA
Regularized Evolution for Image Classifier Architecture Search arXiv:1802.01548
Neural Architecture SearchonNATS-Bench Topology, CIFAR-100
Test Accuracy· 2018-02-05
71.4
best: 71.68 (PPO (Schulman et al., 2017))
Regularized Evolution for Image Classifier Architecture Search arXiv:1802.01548
Neural Architecture SearchonNATS-Bench Topology, ImageNet16-120
Test Accuracy· 2018-02-05
44.76
best: 45.54 (EigenNas (Zhu et al., 2022))
Regularized Evolution for Image Classifier Architecture Search arXiv:1802.01548
AutoMLonNATS-Bench Topology, CIFAR-100
Test Accuracy· 2018-02-05
71.4
best: 71.68 (PPO (Schulman et al., 2017))
Regularized Evolution for Image Classifier Architecture Search arXiv:1802.01548
AutoMLonNATS-Bench Topology, ImageNet16-120
Test Accuracy· 2018-02-05
44.76
best: 45.54 (EigenNas (Zhu et al., 2022))
Regularized Evolution for Image Classifier Architecture Search arXiv:1802.01548