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Neural network pruning is an essential approach for reducing the computational complexity of deep models so that they can be well deployed on resource-limited devices.
Adaptive manifold learning
Jing Wang, Zhenyue Zhang, and Hongyuan Zha · 2004
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Tailoring t-cell receptor signals by proximal negative feedback mechanisms
Oreste Acuto, Vincenzo Di Bartolo, and Frédérique Michel · 2008
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A deadenylation negative feedback mechanism governs meiotic metaphase arrest
Eulalia Belloc and Raúl Méndez · 2008
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Imagenet: A large-scale hierarchical image database
Jia Deng, Wei Dong, Richard Socher, Li-Jia Li, Kai Li, and Li Fei-Fei · 2009
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Learning multiple layers of features from tiny images
Alex Krizhevsky, Geoffrey Hinton, et al · 2009
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Cosine similarity metric learning for face verification
Hieu V Nguyen and Li Bai · 2010
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Speeding-up convolutional neural networks using fine-tuned cp-decomposition
Vadim Lebedev, Yaroslav Ganin, Maksim Rakhuba, Ivan Oseledets, and Victor Lempitsky · 2014
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Fast r-cnn
Ross Girshick · 2015
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Distilling the knowledge in a neural network
Geoffrey Hinton, Oriol Vinyals, and Jeff Dean · 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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Xnor-net: Imagenet classification using binary convolutional neural networks
Mohammad Rastegari, Vicente Ordonez, Joseph Redmon, and Ali Farhadi · 2016
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You only look once: Unified, real-time object detection
Joseph Redmon, Santosh Divvala, Ross Girshick, and Ali Farhadi · 2016
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Learning structured sparsity in deep neural networks
Wei Wen, Chunpeng Wu, Yandan Wang, Yiran Chen, and Hai Li · 2016
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Quantized convolutional neural networks for mobile devices
Jiaxiang Wu, Cong Leng, Yuhang Wang, Qinghao Hu, and Jian Cheng · 2016
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More is less: A more complicated network with less inference complexity
Xuanyi Dong, Junshi Huang, Yi Yang, and Shuicheng Yan · 2017
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Spatiotemporal multiplier networks for video action recognition
Christoph Feichtenhofer, Axel Pinz, and Richard P Wildes · 2017
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Channel pruning for accelerating very deep neural networks
Yihui He, Xiangyu Zhang, and Jian Sun · 2017
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Imagenet classification with deep convolutional neural networks
Alex Krizhevsky, Ilya Sutskever, and Geoffrey E Hinton · 2017
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Learning efficient convolutional networks through network slimming
Zhuang Liu, Jianguo Li, Zhiqiang Shen, Gao Huang, Shoumeng Yan, and Changshui Zhang · 2017
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Fully-adaptive feature sharing in multi-task networks with applications in person attribute classification
Yongxi Lu, Abhishek Kumar, Shuangfei Zhai, Yu Cheng, Tara Javidi, and Rogerio Feris · 2017
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Automatic differentiation in pytorch
Adam Paszke, Sam Gross, Soumith Chintala, Gregory Chanan, Edward Yang, Zachary DeVito, Zeming Lin, Alban Desmaison, Luca Antiga, and Adam Lerer · 2017
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Learning from multiple teacher networks
Shan You, Chang Xu, Chao Xu, and Dacheng Tao · 2017
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Dynamic channel pruning: Feature boosting and suppression
Xitong Gao, Yiren Zhao, Lukasz Dudziak, Robert Mullins, and Cheng-zhong Xu · 2018
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Soft filter pruning for accelerating deep convolutional neural networks
Yang He, Guoliang Kang, Xuanyi Dong, Yanwei Fu, and Yi Yang · 2018
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Deepvs: A deep learning based video saliency prediction approach
Lai Jiang, Mai Xu, Tie Liu, Minglang Qiao, and Zulin Wang · 2018
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Holistic cnn compression via low-rank decomposition with knowledge transfer
Shaohui Lin, Rongrong Ji, Chao Chen, Dacheng Tao, and Jiebo Luo · 2018
Cited alongside, same era.
Accelerating convolutional networks via global & dynamic filter pruning
Shaohui Lin, Rongrong Ji, Yuchao Li, Yongjian Wu, Feiyue Huang, and Baochang Zhang · 2018
Learning student networks via feature embedding
Hanting Chen, Yunhe Wang, Chang Xu, Chao Xu, and Dacheng Tao · 2020
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Discrete model compression with resource constraint for deep neural networks
Shangqian Gao, Feihu Huang, Jian Pei, and Heng Huang · 2020
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Hit-detector: Hierarchical trinity architecture search for object detection
Jianyuan Guo, Kai Han, Yunhe Wang, Chao Zhang, Zhaohui Yang, Han Wu, Xinghao Chen, and Chang Xu · 2020
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Ghostnet: More features from cheap operations
Kai Han, Yunhe Wang, Qi Tian, Jianyuan Guo, Chunjing Xu, and Chang Xu · 2020
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Training binary neural networks through learning with noisy supervision
Kai Han, Yunhe Wang, Yixing Xu, Chunjing Xu, Enhua Wu, and Chang Xu · 2020
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Group sparsity: The hinge between filter pruning and decomposition for network compression
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Cited alongside, same era.
Thinet: pruning cnn filters for a thinner net
Jian-Hao Luo, Hao Zhang, Hong-Yu Zhou, Chen-Wei Xie, Jianxin Wu, and Weiyao Lin · 2018
Cited alongside, same era.
Runtime network routing for efficient image classification
Yongming Rao, Jiwen Lu, Ji Lin, and Jie Zhou · 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.
Image reconstruction by domain-transform manifold learning
Bo Zhu, Jeremiah Z Liu, Stephen F Cauley, Bruce R Rosen, and Matthew S Rosen · 2018
Cited alongside, same era.
Discrimination-aware channel pruning for deep neural networks
Zhuangwei Zhuang, Mingkui Tan, Bohan Zhuang, Jing Liu, Yong Guo, Qingyao Wu, Junzhou Huang, and Jinhui Zhu · 2018
Cited alongside, same era.
Beyond human parts: Dual part-aligned representations for person re-identification
Jianyuan Guo, Yuhui Yuan, Lang Huang, Chao Zhang, Jin-Ge Yao, and Kai Han · 2019
Cited alongside, same era.
Yawei Li, Shuhang Gu, Christoph Mayer, Luc Van Gool, and Radu Timofte · 2020
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Dhp: Differentiable meta pruning via hypernetworks
Yawei Li, Shuhang Gu, Kai Zhang, Luc Van Gool, and Radu Timofte · 2020
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Provable filter pruning for efficient neural networks
Lucas Liebenwein, Cenk Baykal, Harry Lang, Dan Feldman, and Daniela Rus · 2020
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Hrank: Filter pruning using high-rank feature map
Mingbao Lin, Rongrong Ji, Yan Wang, Yichen Zhang, Baochang Zhang, Yonghong Tian, and Ling Shao · 2020
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Dsa: More efficient budgeted pruning via differentiable sparsity allocation
Xuefei Ning, Tianchen Zhao, Wenshuo Li, Peng Lei, Yu Wang, and Huazhong Yang · 2020
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Leveraging filter correlations for deep model compression
Pravendra Singh, Vinay Kumar Verma, Piyush Rai, and Vinay Namboodiri · 2020
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A semi-supervised assessor of neural architectures
Yehui Tang, Yunhe Wang, Yixing Xu, Hanting Chen, Boxin Shi, Chao Xu, Chunjing Xu, Qi Tian, and Chang Xu · 2020
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Scop: Scientific control for reliable neural network pruning
Yehui Tang, Yunhe Wang, Yixing Xu, Dacheng Tao, Chunjing Xu, Chao Xu, and Chang Xu · 2020
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Reborn filters: Pruning convolutional neural networks with limited data
Yehui Tang, Shan You, Chang Xu, Jin Han, Chen Qian, Boxin Shi, Chao Xu, and Changshui Zhang · 2020
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Kernel based progressive distillation for adder neural networks
Yixing Xu, Chang Xu, Xinghao Chen, Wei Zhang, Chunjing Xu, and Yunhe Wang · 2020
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Cars: Continuous evolution for efficient neural architecture search
Zhaohui Yang, Yunhe Wang, Xinghao Chen, Boxin Shi, Chao Xu, Chunjing Xu, Qi Tian, and Chang Xu · 2020
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Searching for low-bit weights in quantized neural networks
Zhaohui Yang, Yunhe Wang, Kai Han, Chunjing Xu, Chao Xu, Dacheng Tao, and Chang Xu · 2020
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Shiftaddnet: A hardware-inspired deep network
Haoran You, Xiaohan Chen, Yongan Zhang, Chaojian Li, Sicheng Li, Zihao Liu, Zhangyang Wang, and Yingyan Lin · 2020
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Greedynas: Towards fast one-shot nas with greedy supernet
Shan You, Tao Huang, Mingmin Yang, Fei Wang, Chen Qian, and Changshui Zhang · 2020
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Locally free weight sharing for network width search
Xiu Su, Shan You, Tao Huang, Fei Wang, Chen Qian, Changshui Zhang, and Chang Xu · 2021
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