Neural Architecture Search with Reinforcement Learning
Citations
9 citations
9 citations
Cites background from "Neural Architecture Search with Rei..."
...Obtaining neural architectures ‘from scratch’ using excessive computational resources via so-called architecture search has been applied for the problem of image classification in [21], [22] but the efficacy for sparse signal recovery is unclear....
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9 citations
Cites background or methods from "Neural Architecture Search with Rei..."
...However, early approaches based on evolution or reinforcement learning take hundreds or thousands of GPU days just for CIFAR10 or Imagenet target datasets [42, 43, 31, 25]....
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...In the pioneering work [42], a RNN controller is adopted to sample architectures, which are trained to obtain accuracy as the reward signal for updating the controller....
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9 citations
Additional excerpts
...Finding the best hyperparameters is something that can be done automatically by autoML [2, 7, 15, 17] or Neural Architecture Search [8, 22, 27, 36]....
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9 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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