方法证据记录
Neural Architecture Search
Neural Architecture Search (NAS), introduced by Zoph and Le in 2017, automatically optimizes architectural decisions such as a network's depth, width, and connection structure instead of hand-designing them. Leading methods in the field include DARTS, ENAS, and Once-for-All.
源记录
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Neural Architecture Search (NAS)
分类方法记录 · ml-model / deep-learning
- Zoph, B. & Le, Q.V. (2017). Neural Architecture Search with Reinforcement Learning. ICLR. · URL
- Liu, H. et al. (2019). DARTS: Differentiable Architecture Search. ICLR. · URL
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