Neural Architecture Search with Reinforcement Learning
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Cites background from "Neural Architecture Search with Rei..."
...The state of the art on the extremely popular and over-optimized ImageNET benchmark also belongs not to a human-designed architecture, but to one produced by an architecture search algorithm [136]....
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...Increasingly, however, researchers are searching for deep neural network architectures automatically with machine learning algorithms [137, 134, 111, 200]....
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...For example, automatically discovered architectures improved performance even on the classic benchmark of CIFAR and the challenging benchmark of ImageNET [79, 137, 134, 111, 200], both of which had already been highly optimized by armies of human scientists....
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...That includes research into encodings (aka representations) [165, 168, 167, 200, 53], search operators, and the production of architectures that are regular [168, 25, 67], modular [26, 67], and hierarchical [106]....
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85 citations
85 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
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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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