Semi-Supervised Neural Architecture Search

Neural architecture search (NAS) relies on a good controller to generate better architectures or predict the accuracy of given architectures. However, training the controller requires both abundant and high-quality pairs of architectures and their accuracy, while it is costly to evaluate an architecture and obtain its accuracy... (read more)

PDF Abstract NeurIPS 2020 PDF NeurIPS 2020 Abstract
TASK DATASET MODEL METRIC NAME METRIC VALUE GLOBAL RANK RESULT BENCHMARK
Neural Architecture Search ImageNet SemiNAS Top-1 Error Rate 23.5 # 15
Accuracy 76.5 # 15

Methods used in the Paper


METHOD TYPE
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