Neural Architecture Search with Reinforcement Learning
Citations
5 citations
5 citations
Cites background or methods from "Neural Architecture Search with Rei..."
...ENAS [21] uses a controller to discover network architectures by searching an optimal subgraph within a large computational graph and shares parameters among child models to enable efficient NAS....
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...Neural Architecture Search (NAS) [32] searches the transferable network blocks via reinforcement learning and outperforms many manually designed network architecture....
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...AutoML refers to automatically learn a suitable machine learning (ML) model for a given task — Neural Architecture Search (NAS) [32] is a subfield of AutoML for deep learning, which searches for optimal hyperparameters of designing a network architecture using reinforcement learning (RL)....
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...There are many works on AutoML to improve the performance of deep neural networks [32, 21, 3]....
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5 citations
5 citations
5 citations
Cites methods from "Neural Architecture Search with Rei..."
...The kernel size and channel depth are optimized using the NASReinforcement Learning method in [48]; and (b) Classification performance (AUC) of HistoNet on selected HTTs at different scan resolutions....
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...Furthermore, we develop a simple and yet efficient Convolutional Neural Network (CNN) architecture called “HistoNet”, guided by the Reinforcement Learning (RL)-based Neural Architecture Search (NAS) [48] as a means to the end goal of domain adaptation....
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...First, we seek the optimal configuration for {w`}6`=1 and {D`} 6 i=1 using the neural architecture search with reinforcement learning algorithm introduced in [48]....
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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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