Neural Architecture Search with Reinforcement Learning
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32 citations
Cites background from "Neural Architecture Search with Rei..."
..., various basic parameters during neural network training, such as initialization of parameters [17], the choice of optimizers [18], even the structure of models [19], etc....
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32 citations
Cites background from "Neural Architecture Search with Rei..."
...In [10], each cell is a normal convolution operation....
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...Figure 3 shows the NAS framework presented in [10]....
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...Existing work has demonstrated that the automatically generated network architectures can achieve close accuracy to the best human-invented architectures on the image classification task [10, 12]....
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...For [10], it searches 20,000 networks and trains these networks across 500 P100 GPUs over 4 days....
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...One of the most successful work is carried out by Google [10], which leverages reinforcement learning to predict hyperparameters to identify specific neural architectures, and utilizes their accuracies as rewards....
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32 citations
32 citations
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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