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The ability to rank candidate architectures is the key to the performance of neural architecture search~(NAS).
Neural architecture search with reinforcement learning
Barret Zoph and Quoc V Le · 2016
Earlier work this paper cites.
Improved regularization of convolutional neural networks with cutout
Terrance DeVries and Graham W Taylor · 2017
Earlier work this paper cites.
Mobilenets: Efficient convolutional neural networks for mobile vision applications
Andrew G Howard, Menglong Zhu, Bo Chen, Dmitry Kalenichenko, Weijun Wang, Tobias Weyand, Marco Andreetto, and Hartwig Adam · 2017
Earlier work this paper cites.
Understanding and simplifying one-shot architecture search
Gabriel Bender, Pieter-Jan Kindermans, Barret Zoph, Vijay Vasudevan, and Quoc Le · 2018
Earlier work this paper cites.
Proxylessnas: Direct neural architecture search on target task and hardware
Han Cai, Ligeng Zhu, and Song Han · 2018
Earlier work this paper cites.
Hierarchical representations for efficient architecture search
Hanxiao Liu, Karen Simonyan, Oriol Vinyals, Chrisantha Fernando, and Koray Kavukcuoglu · 2018
Earlier work this paper cites.
Darts: Differentiable architecture search
Hanxiao Liu, Karen Simonyan, Yiming Yang, and Hanxiao Liu · 2018
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Neural architecture optimization
Renqian Luo, Fei Tian, Tao Qin, and Tie-Yan Liu · 2018
Earlier work this paper cites.
Efficient neural architecture search via parameter sharing
Hieu Pham, Melody Guan, Barret Zoph, Quoc Le, and Jeff Dean · 2018
Cited alongside, same era.
Regularized evolution for image classifier architecture search
Esteban Real, Alok Aggarwal, Yanping Huang, and Quoc V Le · 2018
Cited alongside, same era.
Mobilenetv2: Inverted residuals and linear bottlenecks
Mark Sandler, Andrew Howard, Menglong Zhu, Andrey Zhmoginov, and Liang-Chieh Chen · 2018
Cited alongside, same era.
Snas: Stochastic neural architecture search, 2018
Sirui Xie, Hehui Zheng, Chunxiao Liu, and Liang Lin · 2018
Cited alongside, same era.
Learning transferable architectures for scalable image recognition
Barret Zoph, Vijay Vasudevan, Jonathon Shlens, and Quoc V Le · 2018
Cited alongside, same era.
Progressive differentiable architecture search: Bridging the depth gap between search and evaluation
Single path one-shot neural architecture search with uniform sampling
Zichao Guo, Xiangyu Zhang, Haoyuan Mu, Wen Heng, Zechun Liu, Yichen Wei, and Jian Sun · 2019
Closest in time.
Random search and reproducibility for neural architecture search
Liam Li and Ameet Talwalkar · 2019
Closest in time.
The evolved transformer
David So, Quoc Le, and Chen Liang · 2019
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Single-path nas: Designing hardware-efficient convnets in less than 4 hours
Dimitrios Stamoulis, Ruizhou Ding, Di Wang, Dimitrios Lymberopoulos, Bodhi Priyantha, Jie Liu, and Diana Marculescu · 2019
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Mnasnet: Platform-aware neural architecture search for mobile
Mingxing Tan, Bo Chen, Ruoming Pang, Vijay Vasudevan, Mark Sandler, Andrew Howard, and Quoc V Le · 2019
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Xin Chen, Lingxi Xie, Jun Wu, and Qi Tian · 2019
Cited alongside, same era.
Fast, accurate and lightweight super-resolution with neural architecture search
Xiangxiang Chu, Bo Zhang, Hailong Ma, Ruijun Xu, Jixiang Li, and Qingyuan Li · 2019
Cited alongside, same era.
Nas-fpn: Learning scalable feature pyramid architecture for object detection
Golnaz Ghiasi, Tsung-Yi Lin, and Quoc V Le · 2019
Cited alongside, same era.
Pc-darts: Partial channel connections for memory-efficient differentiable architecture search, 2019
Yuhui Xu, Lingxi Xie, Xiaopeng Zhang, Xin Chen, Guo-Jun Qi, Qi Tian, and Hongkai Xiong · 2019
Closest in time.
Network slimming by slimmable networks: Towards one-shot architecture search for channel numbers
Jiahui Yu and Thomas Huang · 2019
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Bayesnas: A bayesian approach for neural architecture search
Hongpeng Zhou, Minghao Yang, Jun Wang, and Wei Pan · 2019
Closest in time.