Research map / Architectures and efficiency / Neural architecture search
CARS: Continuous Evolution for Efficient Neural Architecture Search
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Measured effects reported in the paper
| What was changed | Where | Measured | Effect |
|---|---|---|---|
| Use pNSGA-III instead of NSGA-III for architecture selection (ablation) | CARS · CIFAR-10 search | retention of larger architectures | Helped |
| Use NSGA-III instead of pNSGA-III for architecture selection (ablation) | CARS · CIFAR-10 search | range of model sizes retained | Hurt |
| Add protection using accuracy-increase speed alongside accuracy and model size (ablation) | CARS architecture selection · CIFAR-10 search | retention of larger models | Helped |
Closest papers by meaning
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- Efficient Few-Shot Neural Architecture Search by Counting the Number of Nonlinear Functions (AAAI 2025 · similarity 0.87)
- Subnet-Aware Dynamic Supernet Training for Neural Architecture Search (CVPR 2025 · similarity 0.87)
- Runtime Analysis of Evolutionary NAS for Multiclass Classification (ICML 2025 · similarity 0.87)
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