Neural Architecture Search with Reinforcement Learning
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Cites background or methods from "Neural Architecture Search with Rei..."
...[50] first proposed the concept of large-scale image classifier searching, which encoded different operations (e....
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...[50] generated the model descriptions of neural networks using a recurrent network and produced higher-accuracy architectures by training the recurrent neural network (RNN) with reinforcement learning....
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4 citations
4 citations
4 citations
4 citations
Cites background from "Neural Architecture Search with Rei..."
...One of the first successes in this field was achieved in [28] where reinforcement learning was applied to discover novel architectures that outperformed human-invented models on a set of tasks such as image classification, object detection, and semantic segmentation....
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References
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"Neural Architecture Search with Rei..." refers methods in this paper
...Along with this success is a paradigm shift from feature designing to architecture designing, i.e., from SIFT (Lowe, 1999), and HOG (Dalal & Triggs, 2005), to AlexNet (Krizhevsky et al., 2012), VGGNet (Simonyan & Zisserman, 2014), GoogleNet (Szegedy et al., 2015), and ResNet (He et al., 2016a)....
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42,067 citations
31,952 citations
"Neural Architecture Search with Rei..." refers methods in this paper
...Along with this success is a paradigm shift from feature designing to architecture designing, i.e., from SIFT (Lowe, 1999), and HOG (Dalal & Triggs, 2005), to AlexNet (Krizhevsky et al., 2012), VGGNet (Simonyan & Zisserman, 2014), GoogleNet (Szegedy et al., 2015), and ResNet (He et al., 2016a)....
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