Neural Architecture Search (NAS)
Automated methods for designing optimal neural network architectures rather than manual design.
In more detail
NAS uses reinforcement learning, evolutionary algorithms, or gradient-based methods to search the architecture space. Reduces manual design effort but requires significant computation. Discovering architectures like EfficientNet and NASNet.
Examples
- Auto-ML systems
- Neural architecture search
- AutoML platforms
Related terms
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