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MANAS: Multi-Agent Neural Architecture Search

3 Sep 2019 • Fabio Maria Carlucci • Pedro M. Esperança • Marco Singh • Victor Gabillon • Antoine Yang • Hang Xu • Zewei Chen • Jun Wang

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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NEURAL ARCHITECTURE SEARCH

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ImageNet

CIFAR-10

Caltech-101

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

MANAS: Multi-Agent Neural Architecture Search

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