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Channel pruning has been identified as an effective approach to constructing efficient network structures.
“Gradient-based learning applied to document recognition,”
Yann LeCun, Léon Bottou, Yoshua Bengio, and Patrick Haffner, · 1998
Earlier work this paper cites.
“Learning multiple layers of features from tiny images,”
Alex Krizhevsky and Geoffrey Hinton, · 2009
Earlier work this paper cites.
“Distributed optimization and statistical learning via the alternating direction method of multipliers,”
Stephen Boyd, Neal Parikh, Eric Chu, Borja Peleato, Jonathan Eckstein, et al., · 2011
Earlier work this paper cites.
“Imagenet classification with deep convolutional neural networks,”
Alex Krizhevsky, Ilya Sutskever, and Geoffrey E Hinton, · 2012
Earlier work this paper cites.
“Facenet: A unified embedding for face recognition and clustering,”
Florian Schroff, Dmitry Kalenichenko, and James Philbin, · 2015
Earlier work this paper cites.
“Learning both weights and connections for efficient neural network,”
Song Han, Jeff Pool, John Tran, and William Dally, · 2015
Earlier work this paper cites.
“Channel-level acceleration of deep face representations,”
Adam Polyak and Lior Wolf, · 2015
Earlier work this paper cites.
“Pruning filters for efficient convnets,”
Hao Li, Asim Kadav, Igor Durdanovic, Hanan Samet, and Hans Peter Graf, · 2016
Earlier work this paper cites.
“Pruning convolutional neural networks for resource efficient inference,”
Pavlo Molchanov, Stephen Tyree, Tero Karras, Timo Aila, and Jan Kautz, · 2016
Cited alongside, same era.
“Mask r-cnn,”
Kaiming He, Georgia Gkioxari, Piotr Dollár, and Ross Girshick, · 2017
Cited alongside, same era.
“Image-to-image translation with conditional adversarial networks,”
Phillip Isola, Jun-Yan Zhu, Tinghui Zhou, and Alexei A Efros, · 2017
Cited alongside, same era.
“Mastering the game of go without human knowledge,”
David Silver, Julian Schrittwieser, Karen Simonyan, Ioannis Antonoglou, Aja Huang, Arthur Guez, Thomas Hubert, Lucas Baker, Matthew Lai, Adrian Bolton, et al., · 2017
Cited alongside, same era.
“Efficient processing of deep neural networks: A tutorial and survey,”
Vivienne Sze, Yu-Hsin Chen, Tien-Ju Yang, and Joel S Emer, · 2017
Cited alongside, same era.
“Fast-converging conditional generative adversarial networks for image synthesis,”
Chengcheng Li, Zi Wang, and Hairong Qi, · 2018
Later among the works it cites.
“Deep reinforcement learning of cell movement in the early stage of c. elegans embryogenesis,”
Zi Wang, Dali Wang, Chengcheng Li, Yichi Xu, Husheng Li, and Zhirong Bao, · 2018
Later among the works it cites.
“A systematic dnn weight pruning framework using alternating direction method of multipliers,”
Tianyun Zhang, Shaokai Ye, Kaiqi Zhang, Jian Tang, Wujie Wen, Makan Fardad, and Yanzhi Wang, · 2018
Later among the works it cites.
“Efficient sparse-winograd convolutional neural networks,”
Xingyu Liu, Jeff Pool, Song Han, and William J Dally, · 2018
Later among the works it cites.
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Jian-Hao Luo, Jianxin Wu, and Weiyao Lin, · 2017
Cited alongside, same era.
“Channel pruning for accelerating very deep neural networks,”
Yihui He, Xiangyu Zhang, and Jian Sun, · 2017
Cited alongside, same era.
“Large scale gan training for high fidelity natural image synthesis,”
Andrew Brock, Jeff Donahue, and Karen Simonyan, · 2018
Cited alongside, same era.
Dongsoo Lee, Daehyun Ahn, Taesu Kim, Pierce I Chuang, and Jae-Joon Kim, · 2018
Later among the works it cites.
“Snip: Single-shot network pruning based on connection sensitivity,”
Namhoon Lee, Thalaiyasingam Ajanthan, and Philip HS Torr, · 2018
Later among the works it cites.
“Progressive weight pruning of deep neural networks using admm,”
Shaokai Ye, Tianyun Zhang, Kaiqi Zhang, Jiayu Li, Kaidi Xu, Yunfei Yang, Fuxun Yu, Jian Tang, Makan Fardad, Sijia Liu, et al., · 2018
Later among the works it cites.