Semi-Supervised Neural Architecture Search

NeurIPS 2020 • Renqian Luo • Xu Tan • Rui Wang • Tao Qin • Enhong Chen • Tie-Yan Liu

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)

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Tasks
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TASK DATASET MODEL METRIC NAME METRIC VALUE GLOBAL RANK RESULT BENCHMARK
Neural Architecture Search ImageNet SemiNAS Top-1 Error Rate 23.5 # 15
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Accuracy 76.5 # 15
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Methods used in the Paper
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