Neural Architecture Search with Reinforcement Learning
Citations
22 citations
Cites methods from "Neural Architecture Search with Rei..."
...By employing the modeling power of deep learning, single-agent reinforcement learning (RL) has started to display, even surpass, human-level intelligence on a wide variety of tasks, ranging from playing the games of Labyrinth [31], Atari [33], and Go [43] to other tasks such as continuous control on locomotions [27], text generation [53], and neural architecture design [54]....
[...]
22 citations
22 citations
22 citations
Cites methods from "Neural Architecture Search with Rei..."
...Since the neural networks are still hard to design a priori, Neural Architecture Search (NAS) has been proposed to design the neural networks automatically based on reinforcement learning [165,166], evolution algorithm [167,168] or gradient-based methods [169,170]....
[...]
21 citations
References
123,388 citations
111,197 citations
55,235 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)....
[...]
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)....
[...]