Neural Architecture Search with Reinforcement Learning
Citations
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Cites background or methods from "Neural Architecture Search with Rei..."
...Some widely used search strategies for NAS are: Random Search, Bayesian Optimization, Evolutionary Methods, Reinforcement Learning, and Gradient Based Methods....
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...Currently, most of the current AAS suffer from high computational cost while searching in a relatively small search space [44],[17],[29]....
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...Most of the algorithms for AAS are either based on reinforcement learning [44],[45],[27], [3] or evolutionary computation [41], [22], [29],[17], [28]....
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...Some widely used search strategies for AAS are: Random Search, Bayesian Optimization [15], Evolutionary Methods [29],[41],[17],[28], Reinforcement Learning [44], [3], [6], [43],[7], [27] and Gradient Based Methods [4], [19], [18]....
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30 citations
30 citations
Cites background from "Neural Architecture Search with Rei..."
...In recent years, neural architecture search (NAS) [4] [23], which...
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30 citations
Cites methods from "Neural Architecture Search with Rei..."
...Neural Architecture Search With reinforcement learning (RL) and evolutionary algorithm (EA) being applied to NAS methods, many works (Zoph & Le, 2016; Zoph et al., 2017; Real et al., 2018) make great progress in promoting the performances of neural networks....
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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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