Neural Architecture Search with Reinforcement Learning
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Cites background from "Neural Architecture Search with Rei..."
..., 2006) or tuning hyperparameters in machine learning algorithms (Zoph and Le, 2016)....
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...Beyond that, it also helps in optimizing financial trading (Nevmyvaka et al., 2006) or tuning hyperparameters in machine learning algorithms (Zoph and Le, 2016)....
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5 citations
5 citations
5 citations
Cites background from "Neural Architecture Search with Rei..."
...presented a seminal work where they introduce the Reinforcement Learning (RL) for NAS [36]....
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...This has drawn researchers’ attention to Neural Architecture Search (NAS), which involves techniques to construct neural networks without the need for profound domain knowledge [22, 26, 1, 36, 37]....
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...Therefore, most of the cloud and desktop-based works focus on optimizing the speed of the search process and the accuracy of neural networks [22, 26, 1, 36, 37, 30, 5, 25, 30, 14, 29]....
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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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