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Neural Architecture Search~(NAS) has attracted increasingly more attention in recent years because of its capability to design deep neural networks automatically.
Comparing biases for minimal network construction with back-propagation
Stephen Hanson and Lorien Pratt · 1988
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A simple weight decay can improve generalization
Anders Krogh and John A Hertz · 1992
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L2 regularization for learning kernels
Corinna Cortes, Mehryar Mohri, and Afshin Rostamizadeh · 2012
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Learning curve prediction with bayesian neural networks
Aaron Klein, Stefan Falkner, Jost Tobias Springenberg, and Frank Hutter · 2016
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Decoupled weight decay regularization
Ilya Loshchilov and Frank Hutter · 2017
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Exploring generalization in deep learning
Behnam Neyshabur, Srinadh Bhojanapalli, David McAllester, and Nathan Srebro · 2017
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Path-level network transformation for efficient architecture search
Han Cai, Jiacheng Yang, Weinan Zhang, Song Han, and Yong Yu · 2018
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Lipschitz regularized deep neural networks generalize and are adversarially robust
Chris Finlay, Jeff Calder, Bilal Abbasi, and Adam Oberman · 2018
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Darts: Differentiable architecture search
Hanxiao Liu, Karen Simonyan, and Yiming Yang · 2018
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Snas: stochastic neural architecture search
Sirui Xie, Hehui Zheng, Chunxiao Liu, and Liang Lin · 2018
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Learning transferable architectures for scalable image recognition
Barret Zoph, Vijay Vasudevan, Jonathon Shlens, and Quoc V Le · 2018
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Learning transferable architectures for scalable image recognition
Barret Zoph, Vijay Vasudevan, Jonathon Shlens, and Quoc V Le · 2018
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Progressive differentiable architecture search: Bridging the depth gap between search and evaluation
Xin Chen, Lingxi Xie, Jun Wu, and Qi Tian · 2019
Cited alongside, same era.
Searching for a robust neural architecture in four gpu hours
Xuanyi Dong and Yi Yang · 2019
Cited alongside, same era.
Darts+: Improved differentiable architecture search with early stopping
Hanwen Liang, Shifeng Zhang, Jiacheng Sun, Xingqiu He, Weiran Huang, Kechen Zhuang, and Zhenguo Li · 2019
Cited alongside, same era.
Regularized evolution for image classifier architecture search
Esteban Real, Alok Aggarwal, Yanping Huang, and Quoc V Le · 2019
Cited alongside, same era.
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
Cited alongside, same era.
Sharpness-aware minimization for efficiently improving generalization
Pierre Foret, Ariel Kleiner, Hossein Mobahi, and Behnam Neyshabur · 2020
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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 · 2020
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Dropnas: Grouped operation dropout for differentiable architecture search
Weijun Hong, Guilin Li, Weinan Zhang, Ruiming Tang, Yunhe Wang, Zhenguo Li, and Yong Yu · 2020
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Dsnas: Direct neural architecture search without parameter retraining
Shoukang Hu, Sirui Xie, Hehui Zheng, Chunxiao Liu, Jianping Shi, Xunying Liu, and Dahua Lin · 2020
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Adapting neural architectures between domains
Yanxi Li, Zhaohui Yang, Yunhe Wang, and Chang Xu · 2020
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Yuhui Xu, Lingxi Xie, Xiaopeng Zhang, Xin Chen, Guo-Jun Qi, Qi Tian, and Hongkai Xiong · 2019
Cited alongside, same era.
Understanding and robustifying differentiable architecture search
Thomas Elsken Arber Zela, Tonmoy Saikia, Yassine Marrakchi, Thomas Brox, and Frank Hutter · 2020
Cited alongside, same era.
Stabilizing differentiable architecture search via perturbation-based regularization
Xiangning Chen and Cho-Jui Hsieh · 2020
Cited alongside, same era.
Darts-: robustly stepping out of performance collapse without indicators
Xiangxiang Chu, Xiaoxing Wang, Bo Zhang, Shun Lu, Xiaolin Wei, and Junchi Yan · 2020
Cited alongside, same era.
Fair darts: Eliminating unfair advantages in differentiable architecture search
Xiangxiang Chu, Tianbao Zhou, Bo Zhang, and Jixiang Li · 2020
Cited alongside, same era.
Nas-bench-201: Extending the scope of reproducible neural architecture search
Xuanyi Dong and Yi Yang · 2020
Cited alongside, same era.
Nas-bench-1shot1: Benchmarking and dissecting one-shot neural architecture search, 2020
Arber Zela, Julien Siems, and Frank Hutter · 2020
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Theory-inspired path-regularized differential network architecture search
Pan Zhou, Caiming Xiong, Richard Socher, and Steven CH Hoi · 2020
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Dots: Decoupling operation and topology in differentiable architecture search
Yu-Chao Gu, Li-Juan Wang, Yun Liu, Yi Yang, Yu-Huan Wu, Shao-Ping Lu, and Ming-Ming Cheng · 2021
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Mixsearch: Searching for domain generalized medical image segmentation architectures
Luyan Liu, Zhiwei Wen, Songwei Liu, Hong-Yu Zhou, Hongwei Zhu, Weicheng Xie, Linlin Shen, Kai Ma, and Yefeng Zheng · 2021
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Rethinking architecture selection in differentiable nas
Ruochen Wang, Minhao Cheng, Xiangning Chen, Xiaocheng Tang, and Cho-Jui Hsieh · 2021
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idarts: Differentiable architecture search with stochastic implicit gradients
Miao Zhang, Steven Su, Shirui Pan, Xiaojun Chang, Ehsan Abbasnejad, and Reza Haffari · 2021
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