Differentiable Architecture Search with Ensemble Gumbel-Softmax

Understand

For network architecture search (NAS), it is crucial but challenging to simultaneously guarantee both effectiveness and efficiency.

• Towards achieving this goal, we develop a differentiable NAS solution, where the search space includes arbitrary feed-forward network consisting of the predefined number of connections.
• Benefiting from a proposed ensemble Gumbel-Softmax estimator, our method optimizes both the architecture of a deep network and its parameters in the same round of backward propagation, yielding an end-to-end mechanism of searching network architectures.
• Extensive experiments on a variety of popular datasets strongly evidence that our method is capable of discovering high-performance architectures, while guaranteeing the requisite efficiency during searching.