Neural Architecture Search with Reinforcement Learning
Citations
61 citations
Cites background or methods from "Neural Architecture Search with Rei..."
...2) Accelerator Design Space: We base our work on CHaiDNN – a library for acceleration of CNNs on System-onchip FPGAs [16]....
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...We found that this gradual increase in threshold makes it easier for the RL controller to learn the structure of high-accuracy CNNs....
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...2 shows the structure of the CNNs within NASBench....
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...Unlike our use of NASBench in previous sections, we have no precomputed results for CIFAR-100 image classification, so we must train all discovered CNNs from scratch....
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...The Pareto-optimal points form concentric accuracy-latency tradeoff curves, each at a different accelerator area – different points on the y-axis represent different CNNs, and different points on the x-axis are different accelerator designs....
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60 citations
Cites background from "Neural Architecture Search with Rei..."
...The second category is about AutoML for Neural Architecture Search (NAS), which has raised much attention since [39], which adopts reinforcement learning approach with recurrent neural network (RNN) to train a large number of candidate models for convergence....
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60 citations
60 citations
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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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