Neural Architecture Search with Reinforcement Learning
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Cites background or methods from "Neural Architecture Search with Rei..."
...Several recent works have proposed automatic learning algorithms for image classification tasks using evolution [1], genetic algorithms [2], and reinforcement learning [3, 4]....
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...[3] used reinforcement learning on a deeper fixed-length architecture, adding one layer at a time....
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Cites methods from "Neural Architecture Search with Rei..."
...In this paper, we follow the widely-used cell-based architecture search space in [49, 44, 11, 31, 34, 33, 51, 52, 50]: A network consists of a pre-defined number of cells [51], which can be either norm cells or reduction cells....
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...For instance, reinforcement learning (RL) based methods [52, 51] search a suitable architecture on CIFAR10 by training and evaluating more than 20, 000 architectures by using 500 GPUs over 4 days....
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...In this paper, we present a unified, fast and effective framework, termed Minimum Importance Pruning (MIP), to find an optimal BPE on a specific architecture search space such as cell-based search space [49, 44, 11, 31, 34, 33, 51, 52], as illustrated in Fig....
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...has shown remarkable performance over manual designs in various computer vision tasks [9, 51, 28, 52, 10, 26]....
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...As established by [51], cell based search space is now well adopted [49, 44, 11, 31, 34, 33, 51, 52], which is predefined and fixed during the architecture search to ensure a fair comparison among different NAS methods....
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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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