Neural Architecture Search with Reinforcement Learning
Citations
17 citations
Cites methods from "Neural Architecture Search with Rei..."
...For the segmentation gate, the state at time t, st, is defined as the concatenation of the input xt, the gate activation signal (GAS) gt extracted from the gates of the GRU in another pre-trained RNN autoencoder [10], and the previous action at−1 taken [19],...
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17 citations
Cites methods from "Neural Architecture Search with Rei..."
...Neural architecture search (NAS) [19, 20, 25] is an representative application of AutoML....
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...Recent work AMC [9] employs the popular deep reinforcement learning (DRL) [19, 20] technique for automatic determination of per-layer pruning rates....
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17 citations
17 citations
Cites background from "Neural Architecture Search with Rei..."
...…(Snoek et al., 2012; Hutter et al., 2011; Bergstra et al., 2011; Hazan et al., 2018; Li et al., 2017) and neural architecture search (NAS) (Baker et al., 2017; Zoph and Le, 2017; Esteban et al., 2017; Elsken et al., 2018) that tries to automate this process by casting it as an optimization problem....
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...We now analyze the generated dataset through the lens of HPO and NAS to obtain a deeper understanding of the properties of the benchmark....
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...In this section we use the generated benchmark to evaluate different HPO and NAS methods....
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...Finally, we compare a variety of well-known HPO and NAS methods from the literature, such as Bayesian optimization, evolutionary algorithms, compressed sensing techniques, a bandit based method and random-search (Section 4)....
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..., 2017) and neural architecture search (NAS) (Baker et al., 2017; Zoph and Le, 2017; Esteban et al., 2017; Elsken et al., 2018) that tries to automate this process by casting it as an optimization problem....
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17 citations
Cites methods from "Neural Architecture Search with Rei..."
...MetaQNN [8] and neural architecture search method (NAS) [9] fall into this class....
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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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