Neural Architecture Search Task

A Neural Architecture Search Task is a model search task for neural network models.

• See: Automated Machine Learning, Artificial Neural Network, Machine Learning, Hyperparameter Optimization.

---

---

References

2020

• (Wikipedia, 2020) ⇒ https://en.wikipedia.org/wiki/Neural_architecture_search Retrieved:2020-6-17.
  • Neural architecture search (NAS) is a technique for automating the design of artificial neural networks (ANN), a widely used model in the field of machine learning. NAS has been used to design networks that are on par or outperform hand-designed architectures. Methods for NAS can be categorized according to the search space, search strategy and performance estimation strategy used:
    • The search space defines the type(s) of ANN that can be designed and optimized.
    • The search strategy defines the approach used to explore the search space.
    • The performance estimation strategy evaluates the performance of a possible ANN from its design (without constructing and training it).
  • NAS is closely related to hyperparameter optimization and is a subfield of automated machine learning (AutoML).

---