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Differentiable Architecture Search (DARTS) has attracted extensive attention due to its efficiency in searching for cell structures.
A new measure of rank correlation
Maurice G Kendall · 1938
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Going deeper with convolutions
Christian Szegedy, Wei Liu, Yangqing Jia, Pierre Sermanet, Scott Reed, Dragomir Anguelov, Dumitru Erhan, Vincent Vanhoucke, and Andrew Rabinovich · 2015
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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
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Densely connected convolutional networks
Gao Huang, Zhuang Liu, Laurens Van Der Maaten, and Kilian Q Weinberger · 2017
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Genetic cnn
Lingxi Xie and Alan Yuille · 2017
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Neural architecture search with reinforcement learning
Barret Zoph and Quoc V Le · 2017
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Understanding and simplifying one-shot architecture search
Gabriel Bender, Pieter-Jan Kindermans, Barret Zoph, Vijay Vasudevan, and Quoc V. Le · 2018
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SMASH: One-shot model architecture search through hypernetworks
Andrew Brock, Theo Lim, J.M. Ritchie, and Nick Weston · 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 Yuille, Jonathan Huang, and Kevin Murphy · 2018
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Hierarchical representations for efficient architecture search
Hanxiao Liu, Karen Simonyan, Oriol Vinyals, Chrisantha Fernando, and Koray Kavukcuoglu · 2018
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Shufflenet v2: Practical guidelines for efficient cnn architecture design
Ningning Ma, Xiangyu Zhang, Hai-Tao Zheng, and Jian Sun · 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
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Shufflenet: An extremely efficient convolutional neural network for mobile devices
Xiangyu Zhang, Xinyu Zhou, Mengxiao Lin, and Jian Sun · 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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ProxylessNAS: Dsearchirect neural architecture search on target task and hardware
Han Cai, Ligeng Zhu, and Song Han · 2019
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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
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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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Fair darts: Eliminating unfair advantages in differentiable architecture search
Xiangxiang Chu, Tianbao Zhou, Bo Zhang, and Jixiang Li · 2019
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One-shot neural architecture search via self-evaluated template network
Xuanyi Dong and Yi Yang · 2019
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Searching for a robust neural architecture in four gpu hours
Xuanyi Dong and Yi Yang · 2019
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Res2net: A new multi-scale backbone architecture
Shanghua Gao, Ming-Ming Cheng, Kai Zhao, Xin-Yu Zhang, Ming-Hsuan Yang, and Philip HS Torr · 2019
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Nas-fpn: Learning scalable feature pyramid architecture for object detection
Golnaz Ghiasi, Tsung-Yi Lin, and Quoc V Le · 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 · 2019
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StacNAS: Towards stable and consistent optimization for differentiable neural architecture search
Guilin Li, Xing Zhang, Zitong Wang, Zhenguo Li, and Tong Zhang · 2019
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Darts+: Improved differentiable architecture search with early stopping
Hanwen Liang, Shifeng Zhang, Jiacheng Sun, Xingqiu He, Weiran Huang, Kechen Zhuang, and Zhenguo Li · 2019
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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Jittor: a novel deep learning framework with meta-operators and unified graph execution
Shi-Min Hu, Dun Liang, Guo-Ye Yang, Guo-Wei Yang, and Wen-Yang Zhou · 2020
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Block-wisely supervised neural architecture search with knowledge distillation
Changlin Li, Jiefeng Peng, Liuchun Yuan, Guangrun Wang, Xiaodan Liang, Liang Lin, and Xiaojun Chang · 2020
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Sgas: Sequential greedy architecture search
Guohao Li, Guocheng Qian, Itzel C Delgadillo, Matthias Muller, Ali Thabet, and Bernard Ghanem · 2020
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Improving one-shot nas by suppressing the posterior fading
Xiang Li, Chen Lin, Chuming Li, Ming Sun, Wei Wu, Junjie Yan, and Wanli Ouyang · 2020
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Neural architecture search for lightweight non-local networks
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Cited alongside, same era.
Auto-deeplab: Hierarchical neural architecture search for semantic image segmentation
Chenxi Liu, Liang-Chieh Chen, Florian Schroff, Hartwig Adam, Wei Hua, Alan L Yuille, and Li Fei-Fei · 2019
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DARTS: Differentiable architecture search
Hanxiao Liu, Karen Simonyan, and Yiming Yang · 2019
Cited alongside, same era.
Pytorch: An imperative style, high-performance deep learning library
Adam Paszke, Sam Gross, Francisco Massa, Adam Lerer, James Bradbury, Gregory Chanan, Trevor Killeen, Zeming Lin, Natalia Gimelshein, Luca Antiga, et al · 2019
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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.
Exploring randomly wired neural networks for image recognition
Saining Xie, Alexander Kirillov, Ross Girshick, and Kaiming He · 2019
Cited alongside, same era.
SNAS: stochastic neural architecture search
Sirui Xie, Hehui Zheng, Chunxiao Liu, and Liang Lin · 2019
Cited alongside, same era.
Yingwei Li, Xiaojie Jin, Jieru Mei, Xiaochen Lian, Linjie Yang, Cihang Xie, Qihang Yu, Yuyin Zhou, Song Bai, and Alan L Yuille · 2020
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Leveraging instance-, image-and dataset-level information for weakly supervised instance segmentation
Yun Liu, Yu-Huan Wu, Pei-Song Wen, Yu-Jun Shi, Yu Qiu, and Ming-Ming Cheng · 2020
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Asap: Architecture search, anneal and prune
Asaf Noy, Niv Nayman, Tal Ridnik, Nadav Zamir, Sivan Doveh, Itamar Friedman, Raja Giryes, and Lihi Zelnik · 2020
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Understanding architectures learnt by cell-based neural architecture search
Yao Shu, Wei Wang, and Shaofeng Cai · 2020
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MergeNAS: Merge operations into one for differentiable architecture search
Xiaoxing Wang, Chao Xue, Junchi Yan, Xiaokang Yang, Yonggang Hu, and Kewei Sun · 2020
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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 · 2020
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Evaluating the search phase of neural architecture search
Kaicheng Yu, Christian Sciuto, Martin Jaggi, Claudiu Musat, and Mathieu Salzmann · 2020
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Understanding and robustifying differentiable architecture search
Arber Zela, Thomas Elsken, Tonmoy Saikia, Yassine Marrakchi, Thomas Brox, and Frank Hutter · 2020
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Rethinking performance estimation in neural architecture search
Xiawu Zheng, Rongrong Ji, Qiang Wang, Qixiang Ye, Zhenguo Li, Yonghong Tian, and Qi Tian · 2020
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Econas: Finding proxies for economical neural architecture search
Dongzhan Zhou, Xinchi Zhou, Wenwei Zhang, Chen Change Loy, Shuai Yi, Xuesen Zhang, and Wanli Ouyang · 2020
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Representative batch normalization with feature calibration
Shang-Hua Gao, Qi Han, Duo Li, Pai Peng, Ming-Ming Cheng, and Pai Peng · 2021
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Global2local: Efficient structure search for video action segmentation
Shang-Hua Gao, Qi Han, Zhong-Yu Li, Pai Peng, Liang Wang, and Ming-Ming Cheng · 2021
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JCS: An explainable covid-19 diagnosis system by joint classification and segmentation
Yu-Huan Wu, Shang-Hua Gao, Jie Mei, Jun Xu, Deng-Ping Fan, Rong-Guo Zhang, and Ming-Ming Cheng · 2021
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Regularized densely-connected pyramid network for salient instance segmentation
Yu-Huan Wu, Yun Liu, Le Zhang, Wang Gao, and Ming-Ming Cheng · 2021
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