DATA: Differentiable ArchiTecture Approximation With Distribution Guided Sampling

Neural architecture search (NAS) is inherently subject to the gap of architectures during searching and validating. To bridge this gap effectively, we develop Differentiable ArchiTecture Approximation (DATA) with Ensemble Gumbel-Softmax (EGS) estimator and Architecture Distribution Constraint (ADC)...

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Vydané v:	IEEE transactions on pattern analysis and machine intelligence Ročník 43; číslo 9; s. 2905 - 2920
Hlavní autori:	Zhang, Xinbang, Chang, Jianlong, Guo, Yiwen, Meng, Gaofeng, Xiang, Shiming, Lin, Zhouchen, Pan, Chunhong
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	New York IEEE 01.09.2021 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Predmet:	Approximation Back propagation Binary codes Bridges Clustering Computer architecture distribution guided sampling ensemble gumbel-softmax Estimation Image classification Image segmentation Learning Mathematical analysis Modelling Neural architecture search(NAS) Optimization Sampling Search problems Searching Task analysis
ISSN:	0162-8828, 1939-3539, 2160-9292, 1939-3539
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