MANAS: Multi-Agent Neural Architecture Search

The Neural Architecture Search (NAS) problem is typically formulated as a graph search problem where the goal is to learn the optimal operations over edges in order to maximise a graph-level global objective. Due to the large architecture parameter space, efficiency is a key bottleneck preventing NAS from its practical use... (read more)

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Methods used in the Paper


METHOD TYPE
Random Search
Hyperparameter Search
Sigmoid Activation
Activation Functions
Tanh Activation
Activation Functions
Softmax
Output Functions
LSTM
Recurrent Neural Networks