Neural Architecture Search with Reinforcement Learning
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Cites methods from "Neural Architecture Search with Rei..."
...Stamoulis et al. (2019) significantly reduced the search costs for NAS by applying a gradient-based search scheme with a superkernel that shares weights for multiple convolutional kernels....
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...Tan et al. (2019) proposed a NAS method to accelerate the inference speed on smartphones by incorporating resource-related constraints into the objective function....
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...Recently, automated frameworks, such as the so-called neural architecture search (NAS) (Zoph & Le, 2017), have been proposed....
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4 citations
4 citations
4 citations
References
123,388 citations
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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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