Neural Architecture Search with Reinforcement Learning
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Cites background from "Neural Architecture Search with Rei..."
...Another approach trains the neural network that generates the network architecture using policy gradient-based reinforcement learning methods [23]....
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...However, these approaches require huge computational resources; several works conducted the experiments using more than 100 GPUs [15,23], as the evaluation of a candidate structure requires model training and takes several hours in the case of DNNs....
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3 citations
Cites background from "Neural Architecture Search with Rei..."
...Neural architecture search Recently, neural architecture search(NAS) [24, 25, 26] has shown great improvement in designing smaller and more accurate network architectures....
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3 citations
Cites background from "Neural Architecture Search with Rei..."
...A work related to ours is [22] proposed by Google Brain team in early 2017....
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...It is noted that the proposed model is different from the one in [22] since:...
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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
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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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