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Neural Architecture Search (NAS) aims to find efficient models for multiple tasks.
Reducibility among combinatorial problems
Richard M. Karp · 1972
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Random search for hyper-parameter optimization
James Bergstra and Yoshua Bengio · 2012
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Designing neural network architectures using reinforcement learning
Bowen Baker, Otkrist Gupta, Nikhil Naik, and Ramesh Raskar · 2017
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On calibration of modern neural networks
Chuan Guo, Geoff Pleiss, Yu Sun, and Kilian Q. Weinberger · 2017
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Semi-supervised classification with graph convolutional networks
Thomas N. Kipf and Max Welling · 2017
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Large-scale evolution of image classifiers
Esteban Real, Sherry Moore, Andrew Selle, Saurabh Saxena, Yutaka Leon Suematsu, Jie Tan, Quoc V. Le, and Alexey Kurakin · 2017
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Genetic CNN
Lingxi Xie and Alan L. Yuille · 2017
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Neural architecture search with reinforcement learning
Barret Zoph and Quoc V. Le · 2017
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To trust or not to trust A classifier
Heinrich Jiang, Been Kim, Melody Y. Guan, and Maya R. Gupta · 2018
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NSGA-NET: A multi-objective genetic algorithm for neural architecture search
Zhichao Lu, Ian Whalen, Vishnu Boddeti, Yashesh D. Dhebar, Kalyanmoy Deb, Erik D. Goodman, and Wolfgang Banzhaf · 2018
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Neural architecture optimization
Renqian Luo, Fei Tian, Tao Qin, Enhong Chen, and Tie-Yan Liu · 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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Exploiting the potential of standard convolutional autoencoders for image restoration by evolutionary search
Masanori Suganuma, Mete Ozay, and Takayuki Okatani · 2018
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Transfer learning with neural automl
Catherine Wong, Neil Houlsby, Yifeng Lu, and Andrea Gesmundo · 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
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.
Learning transferable architectures for scalable image recognition
Barret Zoph, Vijay Vasudevan, Jonathon Shlens, and Quoc V. Le · 2018
Cited alongside, same era.
Task2vec: Task embedding for meta-learning
Alessandro Achille, Michael Lam, Rahul Tewari, Avinash Ravichandran, Subhransu Maji, Charless C. Fowlkes, Stefano Soatto, and Pietro Perona · 2019
Cited alongside, same era.
DARTS: differentiable architecture search
Hanxiao Liu, Karen Simonyan, and Yiming Yang · 2019
Cited alongside, same era.
Continual and multi-task architecture search
Ramakanth Pasunuru and Mohit Bansal · 2019
Nsganetv2: Evolutionary multi-objective surrogate-assisted neural architecture search
Zhichao Lu, Kalyanmoy Deb, Erik D. Goodman, Wolfgang Banzhaf, and Vishnu Naresh Boddeti · 2020
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Neural architecture search with GBDT
Renqian Luo, Xu Tan, Rui Wang, Tao Qin, Enhong Chen, and Tie-Yan Liu · 2020
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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
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Bridging the gap between sample-based and one-shot neural architecture search with BONAS
Han Shi, Renjie Pi, Hang Xu, Zhenguo Li, James T. Kwok, and Tong Zhang · 2020
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NPENAS: neural predictor guided evolution for neural architecture search
Chen Wei, Chuang Niu, Yiping Tang, and Jimin Liang · 2020
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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.
CATCH: context-based meta reinforcement learning for transferrable architecture search
Xin Chen, Yawen Duan, Zewei Chen, Hang Xu, Zihao Chen, Xiaodan Liang, Tong Zhang, and Zhenguo Li · 2020
Cited alongside, same era.
Maximal acyclic subgraphs and closest stable matrices
Aleksandar Cvetkovic and Vladimir Yu. Protasov · 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.
Brp-nas: Prediction-based nas using gcns
Lukasz Dudziak, Thomas Chau, Mohamed Abdelfattah, Royson Lee, Hyeji Kim, and Nicholas Lane · 2020
Cited alongside, same era.
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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
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Transnas-bench-101: Improving transferability and generalizability of cross-task neural architecture search
Yawen Duan, Xin Chen, Hang Xu, Zewei Chen, Xiaodan Liang, Tong Zhang, and Zhenguo Li · 2021
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Pointwise binary classification with pairwise confidence comparisons
Lei Feng, Senlin Shu, Nan Lu, Bo Han, Miao Xu, Gang Niu, Bo An, and Masashi Sugiyama · 2021
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Rapid neural architecture search by learning to generate graphs from datasets
Hayeon Lee, Eunyoung Hyung, and Sung Ju Hwang · 2021
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Bossnas: Exploring hybrid cnn-transformers with block-wisely self-supervised neural architecture search
Changlin Li, Tao Tang, Guangrun Wang, Jiefeng Peng, Bing Wang, Xiaodan Liang, and Xiaojun Chang · 2021
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Nas-bench-360: Benchmarking diverse tasks for neural architecture search
Renbo Tu, Mikhail Khodak, Nicholas Roberts, and Ameet Talwalkar · 2021
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Stronger nas with weaker predictors
Junru Wu, Xiyang Dai, Dongdong Chen, Yinpeng Chen, Mengchen Liu, Ye Yu, Zhangyang Wang, Zicheng Liu, Mei Chen, and Lu Yuan · 2021
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Renas: Relativistic evaluation of neural architecture search
Yixing Xu, Yunhe Wang, Kai Han, Yehui Tang, Shangling Jui, Chunjing Xu, and Chang Xu · 2021
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