Neural Architecture Search with Reinforcement Learning
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Cites background or methods from "Neural Architecture Search with Rei..."
...Based on the core algorithmic principle operating during the search, NAS can be divided into four categories: (i) reinforcement learning-based on an actor-critic framework [1]...
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...Current NAS methods are already able to automatically find better neural architectures, in comparison to hand-made NNs [1]–[3], [5]....
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...I. INTRODUCTION Neural networks (NNs) have demonstrated their great potential in a wide range of artificial intelligence tasks such as image classification, object detection or speech recognition [1]–[3]....
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...Additionally, all of the evaluated NNs shared the same evaluation hyperparameters and in the future we want to investigate an approach which can automatically determine suitable hyperparameters for the found architecture....
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...Neural networks (NNs) have demonstrated their great potential in a wide range of artificial intelligence tasks such as image classification, object detection or speech recognition [1]–[3]....
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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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"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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