Research map / Architectures and efficiency / Neural architecture search
Towards modular and programmable architecture search
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Measured effects reported in the paper
| What was changed | Where | Measured | Effect |
|---|---|---|---|
| Use Nasbench instead of Genetic as the search space | Random architecture search · Search space experiments | test accuracy: 90.07 -> 94.59 | Helped |
| Use Flat instead of Genetic as the search space | Random architecture search · Search space experiments | test accuracy: 90.07 -> 93.58 | Helped |
| Use Nasnet instead of Genetic as the search space | Random architecture search · Search space experiments | test accuracy: 90.07 -> 93.77 | Helped |
| Change the search algorithm while holding the search space fixed | Genetic search space · Search algorithm experiments | test accuracy: Random 91.61\pm0.67; MCTS 91.45 \pm 0.11; SMBO 91.93 \pm 1.03; Evolution 91.32 \pm 0.50 | No clear effect |
Closest papers by meaning
- Construction of Hierarchical Neural Architecture Search Spaces based on Context-free Grammars (NeurIPS 2023 · similarity 0.91)
- einspace: Searching for Neural Architectures from Fundamental Operations (NeurIPS 2024 · similarity 0.90)
- Neural Architecture Search on ImageNet in Four GPU Hours: A Theoretically Inspired Perspective (ICLR 2021 · similarity 0.89)
- Towards Improving the Consistency, Efficiency, and Flexibility of Differentiable Neural Architecture Search (CVPR 2021 · similarity 0.89)
- Towards Neural Architecture Search through Hierarchical Generative Modeling (ICML 2024 · similarity 0.88)
- RZ-NAS: Enhancing LLM-guided Neural Architecture Search via Reflective Zero-Cost Strategy (ICML 2025 · similarity 0.88)
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