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This paper addresses the efficiency challenge of Neural Architecture Search (NAS) by formulating the task as a ranking problem.
On neural architecture search for resource-constrained hardware platforms
Qing Lu, Weiwen Jiang, Xiaowei Xu, Yiyu Shi, and Jingtong Hu. 2019 · 1911
Earlier work this paper cites.
Random forests
Leo Breiman. 2001 · 2001
Earlier work this paper cites.
NPENAS: neural predictor guided evolution for neural architecture search
Chen Wei, Chuang Niu, Yiping Tang, and Jimin Liang. 2020 · 2003
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Learning to rank using gradient descent
Christopher J. C. Burges, Tal Shaked, Erin Renshaw, Ari Lazier, Matt Deeds, Nicole Hamilton, and Gregory N. Hullender. 2005 · 2005
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Efficient ranking from pairwise comparisons
Fabian L. Wauthier, Michael I. Jordan, and Nebojsa Jojic. 2013 · 2013
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Lightgbm: A highly efficient gradient boosting decision tree
Guolin Ke, Qi Meng, Thomas Finley, Taifeng Wang, Wei Chen, Weidong Ma, Qiwei Ye, and Tie-Yan Liu. 2017 · 2017
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Pointer sentinel mixture models
Stephen Merity, Caiming Xiong, James Bradbury, and Richard Socher. 2017 · 2017
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Attention is all you need
Ashish Vaswani, Noam Shazeer, Niki Parmar, Jakob Uszkoreit, Llion Jones, Aidan N. Gomez, Lukasz Kaiser, and Illia Polosukhin. 2017 · 2017
Earlier work this paper cites.
Accelerating neural architecture search using performance prediction
Bowen Baker, Otkrist Gupta, Ramesh Raskar, and Nikhil Naik. 2018 · 2018
Earlier work this paper cites.
Efficient architecture search by network transformation
Han Cai, Tianyao Chen, Weinan Zhang, Yong Yu, and Jun Wang. 2018 · 2018
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Progressive neural architecture search
Chenxi Liu, Barret Zoph, Maxim Neumann, Jonathon Shlens, Wei Hua, Li-Jia Li, Li Fei-Fei, Alan L. Yuille, Jonathan Huang, and Kevin Murphy. 2018 · 2018
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Efficient neural architecture search via parameter sharing
Hieu Pham, Melody Y. Guan, Barret Zoph, Quoc V. Le, and Jeff Dean. 2018 · 2018
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Self-attention with relative position representations
Peter Shaw, Jakob Uszkoreit, and Ashish Vaswani. 2018 · 2018
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Practical block-wise neural network architecture generation
Zhao Zhong, Junjie Yan, Wei Wu, Jing Shao, and Cheng-Lin Liu. 2018 · 2018
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Learning transferable architectures for scalable image recognition
Barret Zoph, Vijay Vasudevan, Jonathon Shlens, and Quoc V. Le. 2018 · 2018
Cited alongside, same era.
Adaptive input representations for neural language modeling
Alexei Baevski and Michael Auli. 2019 · 2019
Cited alongside, same era.
Proxylessnas: Direct neural architecture search on target task and hardware
Han Cai, Ligeng Zhu, and Song Han. 2019 · 2019
Cited alongside, same era.
Transformer-XL: Attentive language models beyond a fixed-length context
Zihang Dai, Zhilin Yang, Yiming Yang, Jaime Carbonell, Quoc Le, and Ruslan Salakhutdinov. 2019 · 2019
Cited alongside, same era.
All models are wrong, but many are useful: Learning a variable’s importance by studying an entire class of prediction models simultaneously
Aaron Fisher, Cynthia Rudin, and Francesca Dominici. 2019 · 2019
Cited alongside, same era.
Adabert: Task-adaptive BERT compression with differentiable neural architecture search
Daoyuan Chen, Yaliang Li, Minghui Qiu, Zhen Wang, Bofang Li, Bolin Ding, Hongbo Deng, Jun Huang, Wei Lin, and Jingren Zhou. 2020 · 2020
Later among the works it cites.
BRP-NAS: prediction-based NAS using gcns
Lukasz Dudziak, Thomas C. P. Chau, Mohamed S. Abdelfattah, Royson Lee, Hyeji Kim, and Nicholas D. Lane. 2020 · 2020
Later among the works it cites.
Searching better architectures for neural machine translation
Yang Fan, Fei Tian, Yingce Xia, Tao Qin, Xiang-Yang Li, and Tie-Yan Liu. 2020 · 2020
Later among the works it cites.
The NiuTrans system for WNGT 2020 efficiency task
Chi Hu, Bei Li, Yinqiao Li, Ye Lin, Yanyang Li, Chenglong Wang, Tong Xiao, and Jingbo Zhu. 2020 · 2020
Later among the works it cites.
Learning architectures from an extended search space for language modeling
Yinqiao Li, Chi Hu, Yuhao Zhang, Nuo Xu, Yufan Jiang, Tong Xiao, Jingbo Zhu, Tongran Liu, and Changliang Li. 2020 · 2020
Later among the works it cites.
alphaXiv searches the wider corpus for related work and actual follow-ups.
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Improved differentiable architecture search for language modeling and named entity recognition
Yufan Jiang, Chi Hu, Tong Xiao, Chunliang Zhang, and Jingbo Zhu. 2019 · 2019
Cited alongside, same era.
DARTS: differentiable architecture search
Hanxiao Liu, Karen Simonyan, and Yiming Yang. 2019 · 2019
Cited alongside, same era.
Performance prediction based on neural architecture features
D. Long, S. Zhang, and Y. Zhang. 2019 · 2019
Cited alongside, same era.
Regularized evolution for image classifier architecture search
Esteban Real, Alok Aggarwal, Yanping Huang, and Quoc V. Le. 2019 · 2019
Cited alongside, same era.
The evolved transformer
David R. So, Quoc V. Le, and Chen Liang. 2019 · 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 · 2019
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Learning deep transformer models for machine translation
Qiang Wang, Bei Li, Tong Xiao, Jingbo Zhu, Changliang Li, Derek F. Wong, and Lidia S. Chao. 2019 · 2019
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A generic graph-based neural architecture encoding scheme for predictor-based NAS
Xuefei Ning, Yin Zheng, Tianchen Zhao, Yu Wang, and Huazhong Yang. 2020 · 2020
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Improving transformer models by reordering their sublayers
Ofir Press, Noah A. Smith, and Omer Levy. 2020 · 2020
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HAT: Hardware-aware transformers for efficient natural language processing
Hanrui Wang, Zhanghao Wu, Zhijian Liu, Han Cai, Ligeng Zhu, Chuang Gan, and Song Han. 2020 · 2020
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Neural predictor for neural architecture search
Wei Wen, Hanxiao Liu, Yiran Chen, Hai Helen Li, Gabriel Bender, and Pieter-Jan Kindermans. 2020 · 2020
Later among the works it cites.
On layer normalization in the transformer architecture
Ruibin Xiong, Yunchang Yang, Di He, Kai Zheng, Shuxin Zheng, Chen Xing, Huishuai Zhang, Yanyan Lan, Liwei Wang, and Tie-Yan Liu. 2020 · 2020
Later among the works it cites.
An efficient transformer decoder with compressed sub-layers
Yanyang Li, Ye Lin, Tong Xiao, and Jingbo Zhu. 2021 · 2021
Closest in time.
Autodropout: Learning dropout patterns to regularize deep networks
Hieu Pham and Quoc V. Le. 2021 · 2021
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Memory-efficient differentiable transformer architecture search
Yuekai Zhao, Li Dong, Yelong Shen, Zhihua Zhang, Furu Wei, and Weizhu Chen. 2021 · 2021
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Weight distillation: Transferring the knowledge in neural network parameters
Ye Lin, Yanyang Li, Ziyang Wang, Bei Li, Quan Du, Tong Xiao, and Jingbo Zhu. 2021 · 2088
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