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arXiv · 1905.01786

Differentiable Architecture Search with Ensemble Gumbel-Softmax

Jianlong Chang·Xinbang Zhang·Yiwen Guo·Gaofeng Meng·Shiming Xiang·Chunhong Pan
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Abstract

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.

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Jianlong Chang, Xinbang Zhang, Yiwen Guo, Gaofeng Meng, Shiming Xiang, Chunhong Pan. 2019-05-06. Differentiable Architecture Search with Ensemble Gumbel-Softmax. https://arxiv.org/abs/1905.01786

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