Neural Architecture Search with Reinforcement Learning
Citations
8 citations
8 citations
Cites background from "Neural Architecture Search with Rei..."
...In the DL community, there are a few empirically motivated guidelines for choosing hyper parameters [11; 14; 22; 60; 97], as well automated attempts for hyper parameter and architecture search architecture [15; 16; 139; 184]....
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8 citations
8 citations
Cites methods from "Neural Architecture Search with Rei..."
...The major search strategies (algorithms)[25] include random search[27], reinforcement learning[43], evolutionary[44], Bayesian optimization[45], and gradient-based method[46]....
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8 citations
Cites background from "Neural Architecture Search with Rei..."
...Motivated by the prosperous research on network architecture search (NAS) [28]–[35], there are recent research [17], [36]– [38] of automatic search of hyperparameters in weight pruning....
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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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