Research map / Architectures and efficiency / Neural architecture search
SNAS: stochastic neural architecture search
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Measured effects reported in the paper
| What was changed | Where | Measured | Effect |
|---|---|---|---|
| Increase the resource constraint from mild to moderate (ablation) | SNAS · CIFAR-10 | test error (%): 2.98 -> 2.85 $\pm$ 0.02 | Helped |
| Increase the resource constraint from moderate to aggressive (ablation) | SNAS · CIFAR-10 | test error (%): 2.85 $\pm$ 0.02 -> 3.10 $\pm$ 0.04 | Hurt |
| Use stochastic architecture sampling instead of DARTS's deterministic attention, retaining the derived child architecture during validation | SNAS · CIFAR-10 child network validation, without fine-tuning | accuracy (%): 54.66 -> 90.67 | Helped |
Closest papers by meaning
- Adaptive Stochastic Natural Gradient Method for One-Shot Neural Architecture Search (ICML 2019 · similarity 0.91)
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- Towards Neural Architecture Search through Hierarchical Generative Modeling (ICML 2024 · similarity 0.90)
- EG-NAS: Neural Architecture Search with Fast Evolutionary Exploration (AAAI 2024 · similarity 0.90)
- Boosting Order-Preserving and Transferability for Neural Architecture Search: a Joint Architecture Refined Search and Fine-tuning Approach (CVPR 2024 · similarity 0.89)
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