AutoHAS: Efficient Hyperparameter and Architecture Search

Deep learning models often require extensive efforts in optimizing hyperparameters and architectures. Standard hyperparameter optimization methods are expensive because of their multi-trial nature: different configurations are tried separately to find the best... (read more)

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Methods used in the Paper


METHOD TYPE
DARTS
Neural Architecture Search
REINFORCE
Policy Gradient Methods
Random Search
Hyperparameter Search