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Neural architecture search (NAS) has made tremendous progress in the automatic design of effective neural network structures but suffers from a heavy computational burden.
“Estimates of the regression coefficient based on kendall’s tau,”
Pranab Kumar Sen, · 1968
Earlier work this paper cites.
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“Neural architecture search with reinforcement learning,”
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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
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“Fairnas: Rethinking evaluation fairness of weight sharing neural architecture search,”
Xiangxiang Chu, Bo Zhang, Ruijun Xu, and Jixiang Li, · 2019
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Xuanyi Dong and Yezhou Yang, · 2019
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“PC-DARTS: partial channel connections for memory-efficient architecture search,”
Yuhui Xu, Lingxi Xie, Xiaopeng Zhang, Xin Chen, Guo-Jun Qi, Qi Tian, and Hongkai Xiong, · 2019
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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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“Block proposal neural architecture search,”
Jiaheng Liu, Shunfeng Zhou, Yichao Wu, Ken Chen, Wanli Ouyang, and Dong Xu, · 2020
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“Explicit connection distillation,”
Lujun Li, Yikai Wang, Anbang Yao, Yi Qian, Xiao Zhou, and Ke He, · 2020
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Xuanyi Dong and Yi Yang, · 2020
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“Dsnas: Direct neural architecture search without parameter retraining,”
Shoukang Hu, S. Xie, Hehui Zheng, C. Liu, Jianping Shi, Xunying Liu, and D. Lin, · 2020
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“Zero-cost proxies for lightweight nas,”
Mohamed Saleh Abdelfattah, Abhinav Mehrotra, Lukasz Dudziak, and Nicholas D. Lane, · 2021
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“Zen-nas: A zero-shot nas for high-performance image recognition,”
“Landmark regularization: Ranking guided super-net training in neural architecture search,”
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“Epe-nas: Efficient performance estimation without training for neural architecture search,”
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“Prior-guided one-shot neural architecture search,”
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“Gp-nas-ensemble: a model for the nas performance prediction,”
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Zimian Wei, Hengyue Pan, Lujun Li Li, Menglong Lu, Xin Niu, Peijie Dong, and Dongsheng Li, · 2022
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Ming Lin, Pichao Wang, Zhenhong Sun, Hesen Chen, Xiuyu Sun, Qi Qian, Hao Li, and Rong Jin, · 2021
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“Neural architecture search without training,”
Joseph Charles Mellor, Jack Turner, Amos J. Storkey, and Elliot J. Crowley, · 2021
Cited alongside, same era.
“Improving one-shot nas with shrinking-and-expanding supernet,”
Yiming Hu, Xingang Wang, Lujun Li, and Qingyi Gu, · 2021
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“Evaluating efficient performance estimators of neural architectures,”
Xuefei Ning, Changcheng Tang, Wenshuo Li, Zixuan Zhou, Shuang Liang, Huazhong Yang, and Yu Wang, · 2021
Cited alongside, same era.
“Ranknas: Efficient neural architecture search by pairwise ranking,”
Chi Hu, Chenglong Wang, Xiangnan Ma, Xia Meng, Yinqiao Li, Tong Xiao, Jingbo Zhu, and Changliang Li, · 2021
Cited alongside, same era.
“Rank-nosh: Efficient predictor-based architecture search via non-uniform successive halving,”
Ruochen Wang, Xiangning Chen, Minhao Cheng, Xiaocheng Tang, and Cho-Jui Hsieh, · 2021
Cited alongside, same era.
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“Activation modulation and recalibration scheme for weakly supervised semantic segmentation,”
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“Self-regulated feature learning via teacher-free feature distillation,”
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“Boosting online feature transfer via separable feature fusion.,”
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“Shadow knowledge distillation: Bridging offline and online knowledge transfer,”
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“Teacher-free distillation via regularizing intermediate representation,”
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