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Searching techniques in most of existing neural architecture search (NAS) algorithms are mainly dominated by differentiable methods for the efficiency reason.
An evolutionary many-objective optimization algorithm using reference-point-based nondominated sorting approach, part i: Solving problems with box constraints
Kalyanmoy Deb and Himanshu Jain · 2014
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Fast r-cnn
Ross Girshick · 2015
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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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Deep residual learning for image recognition
Kaiming He, Xiangyu Zhang, Shaoqing Ren, and Jian Sun · 2016
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Binarized neural networks
Itay Hubara, Matthieu Courbariaux, Daniel Soudry, Ran El-Yaniv, and Yoshua Bengio · 2016
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Cnnpack: packing convolutional neural networks in the frequency domain
Yunhe Wang, Chang Xu, Shan You, Dacheng Tao, and Chao Xu · 2016
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Morphnet: Fast & simple resource-constrained structure learning of deep networks
Ariel Gordon, Elad Eban, Ofir Nachum, Bo Chen, Tien-Ju Yang, and Edward Choi · 2017
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Mask r-cnn
Kaiming He, Georgia Gkioxari, Piotr Dollár, and Ross Girshick · 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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Nemo : Neuro-evolution with multiobjective optimization of deep neural network for speed and accuracy
Ye-Hoon Kim, Bhargava Reddy, Sojung Yun, and Chanwon Seo · 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 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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Dpp-net: Device-aware progressive search for pareto-optimal neural architectures
Jin-Dong Dong, An-Chieh Cheng, Da-Cheng Juan, Wei Wei, and Min Sun · 2018
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Simple and efficient architecture search for convolutional neural networks
Thomas Elsken, Jan Hendrik Metzen, and Frank Hutter · 2018
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Monas: Multi-objective neural architecture search using reinforcement learning
Chi-Hung Hsu, Shu-Huan Chang, Da-Cheng Juan, Jia-Yu Pan, Yu-Ting Chen, Wei Wei, and Shih-Chieh Chang · 2018
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Accelerating convolutional networks via global & dynamic filter pruning
Shaohui Lin, Rongrong Ji, Yuchao Li, Yongjian Wu, Feiyue Huang, and Baochang Zhang · 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
Cited alongside, same era.
Efficient neural architecture search via parameter sharing
Hieu Pham, Melody Y Guan, Barret Zoph, Quoc V Le, and Jeff Dean · 2018
Cited alongside, same era.
Mobilenetv2: Inverted residuals and linear bottlenecks
Mark Sandler, Andrew Howard, Menglong Zhu, Andrey Zhmoginov, and Liang-Chieh Chen · 2018
Cited alongside, same era.
Mnasnet: Platform-aware neural architecture search for mobile
Mingxing Tan, Bo Chen, Ruoming Pang, Vijay Vasudevan, and Quoc V Le · 2018
Cited alongside, same era.
Learning versatile filters for efficient convolutional neural networks
Yunhe Wang, Chang Xu, Chunjing Xu, Chao Xu, and Dacheng Tao · 2018
Cited alongside, same era.
Practical block-wise neural network architecture generation
Zhao Zhong, Junjie Yan, Wei Wu, Jing Shao, and Cheng-Lin Liu · 2018
Holistic cnn compression via low-rank decomposition with knowledge transfer
Shaohui Lin, Rongrong Ji, Chao Chen, Dacheng Tao, and Jiebo Luo · 2019
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Towards optimal structured cnn pruning via generative adversarial learning
Shaohui Lin, Rongrong Ji, Chenqian Yan, Baochang Zhang, Liujuan Cao, Qixiang Ye, Feiyue Huang, and David Doermann · 2019
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Darts: Differentiable architecture search
Hanxiao Liu, Karen Simonyan, and Yiming Yang · 2019
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Nsga-net: A multi-objective genetic algorithm for neural architecture search
Zhichao Lu, Ian Whalen, Vishnu Boddeti, Yashesh Dhebar, Kalyanmoy Deb, Erik Goodman, and Wolfgang Banzhaf · 2019
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Auto-reid: Searching for a part-aware convnet for person re-identification
Ruijie Quan, Xuanyi Dong, Yu Wu, Linchao Zhu, and Yi Yang · 2019
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Regularized evolution for image classifier architecture search
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Cited alongside, same era.
Resource-efficient neural architect
Yanqi Zhou, Siavash Ebrahimi, Sercan Ö Arık, Haonan Yu, Hairong Liu, and Greg Diamos · 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.
Proxylessnas: Direct neural architecture search on target task and hardware
Han Cai, Ligeng Zhu, and Song Han · 2019
Cited alongside, same era.
Probabilistic neural architecture search
Francesco Paolo Casale, Jonathan Gordon, and Nicolo Fusi · 2019
Cited alongside, same era.
Data-free learning of student networks
Hanting Chen, Yunhe Wang, Chang Xu, Zhaohui Yang, Chuanjian Liu, Boxin Shi, Chunjing Xu, Chao Xu, and Qi Tian · 2019
Cited alongside, same era.
Progressive darts: Bridging the optimization gap for nas in the wild
Xin Chen, Lingxi Xie, Jun Wu, and Qi Tian · 2019
Cited alongside, same era.
Esteban Real, Alok Aggarwal, Yanping Huang, and Quoc V Le · 2019
Closest in time.
Searching for accurate binary neural architectures
Mingzhu Shen, Kai Han, Chunjing Xu, and Yunhe Wang · 2019
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Co-evolutionary compression for unpaired image translation
Han Shu, Yunhe Wang, Xu Jia, Kai Han, Hanting Chen, Chunjing Xu, Qi Tian, and Chang Xu · 2019
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Fbnet: Hardware-aware efficient convnet design via differentiable neural architecture search
Bichen Wu, Xiaoliang Dai, Peizhao Zhang, Yanghan Wang, Fei Sun, Yiming Wu, Yuandong Tian, Peter Vajda, Yangqing Jia, and Kurt Keutzer · 2019
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Snas: stochastic neural architecture search
Sirui Xie, Hehui Zheng, Chunxiao Liu, and Liang Lin · 2019
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Resource constrained neural network architecture search
Yunyang Xiong, Ronak Mehta, and Vikas Singh · 2019
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Positive-unlabeled compression on the cloud
Yixing Xu, Yunhe Wang, Hanting Chen, Kai Han, Chunjing Xu, Dacheng Tao, and Chang Xu · 2019
Closest in time.
Legonet: Efficient convolutional neural networks with lego filters
Zhaohui Yang, Yunhe Wang, Chuanjian Liu, Hanting Chen, Chunjing Xu, Boxin Shi, Chao Xu, and Chang Xu · 2019
Closest in time.
Nas-bench-101: Towards reproducible neural architecture search
Chris Ying, Aaron Klein, Esteban Real, Eric Christiansen, Kevin Murphy, and Frank Hutter · 2019
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Autoslim: Towards one-shot architecture search for channel numbers
Jiahui Yu and Thomas Huang · 2019
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Universally slimmable networks and improved training techniques
Jiahui Yu and Thomas S. Huang · 2019
Closest in time.
Slimmable neural networks
Jiahui Yu, Linjie Yang, Ning Xu, Jianchao Yang, and Thomas Huang · 2019
Closest in time.
Efficient residual dense block search for image super-resolution
Dehua Song, Chang Xu, Xu Jia, Yiyi Chen, Chunjing Xu, and Yunhe Wang · 2020
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Fsnet: Compression of deep convolutional neural networks by filter summary
Yingzhen Yang, Jiahui Yu, Nebojsa Jojic, Jun Huan, and Thomas S. Huang · 2020
Closest in time.