Fetching the paper…
Reading the bibliography…
Compressing convolutional neural networks (CNNs) is essential for transferring the success of CNNs to a wide variety of applications to mobile devices.
Optimization by simulated annealing
Scott Kirkpatrick, C Daniel Gelatt, Mario P Vecchi, et al · 1983
Earlier work this paper cites.
Gradient-based learning applied to document recognition
Yann LeCun, Léon Bottou, Yoshua Bengio, and Patrick Haffner · 1998
Earlier work this paper cites.
A fast and elitist multiobjective genetic algorithm: Nsga-ii
Kalyanmoy Deb, Amrit Pratap, Sameer Agarwal, and TAMT Meyarivan · 2002
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.
Provable bounds for learning some deep representations
Sanjeev Arora, Aditya Bhaskara, Rong Ge, and Tengyu Ma · 2014
Earlier work this paper cites.
Exploiting linear structure within convolutional networks for efficient evaluation
Emily L Denton, Wojciech Zaremba, Joan Bruna, Yann LeCun, and Rob Fergus · 2014
Earlier work this paper cites.
Rich feature hierarchies for accurate object detection and semantic segmentation
Ross Girshick, Jeff Donahue, Trevor Darrell, and Jitendra Malik · 2014
Earlier work this paper cites.
Fixed-point feedforward deep neural network design using weights+ 1, 0, and- 1
Kyuyeon Hwang and Wonyong Sung · 2014
Earlier work this paper cites.
Training deep neural networks with binary weights during propagations
Matthieu Courbariaux, Yoshua Bengio, and Jean-Pierre Binaryconnect David · 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
Cited alongside, same era.
Deep residual learning for image recognition
Kaiming He, Xiangyu Zhang, Shaoqing Ren, and Jian Sun · 2015
Cited alongside, same era.
Sparse convolutional neural networks
Baoyuan Liu, Min Wang, Hassan Foroosh, Marshall Tappen, and Marianna Pensky · 2015
Cited alongside, same era.
Faster r-cnn: Towards real-time object detection with region proposal networks
Shaoqing Ren, Kaiming He, Ross Girshick, and Jian Sun · 2015
Cited alongside, same era.
Imagenet large scale visual recognition challenge
Olga Russakovsky, Jia Deng, Hao Su, Jonathan Krause, Sanjeev Satheesh, Sean Ma, Zhiheng Huang, Andrej Karpathy, Aditya Khosla, Michael Bernstein, et al · 2015
Cited alongside, same era.
Image super-resolution using deep convolutional networks
Chao Dong, Chen Change Loy, Kaiming He, and Xiaoou Tang · 2016
Later among the works it cites.
Perforatedcnns: Acceleration through elimination of redundant convolutions
Michael Figurnov, Dmitry Vetrov, and Pushmeet Kohli · 2016
Later among the works it cites.
Deep compression: Compressing deep neural networks with pruning, trained quantization and huffman coding
Song Han, Huizi Mao, and William J Dally · 2016
Later among the works it cites.
Network trimming: A data-driven neuron pruning approach towards efficient deep architectures
Hengyuan Hu, Rui Peng, Yu-Wing Tai, and Chi-Keung Tang · 2016
Later among the works it cites.
Xnor-net: Imagenet classification using binary convolutional neural networks
Mohammad Rastegari, Vicente Ordonez, Joseph Redmon, and Ali Farhadi · 2016
Later among the works it cites.
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
Karen Simonyan and Andrew Zisserman · 2015
Cited alongside, same era.
Matconvnet: Convolutional neural networks for matlab
Andrea Vedaldi and Karel Lenc · 2015
Cited alongside, same era.
Binarynet: Training deep neural networks with weights and activations constrained to+ 1 or-1
Matthieu Courbariaux and Yoshua Bengio · 2016
Cited alongside, same era.
Cnnpack: Packing convolutional neural networks in the frequency domain
Yunhe Wang, Chang Xu, Shan You, Dacheng Tao, and Chao Xu · 2016
Later among the works it cites.
Learning structured sparsity in deep neural networks
Wei Wen, Chunpeng Wu, Yandan Wang, Yiran Chen, and Hai Li · 2016
Later among the works it cites.
Large-scale evolution of image classifiers
Esteban Real, Sherry Moore, Andrew Selle, Saurabh Saxena, Yutaka Leon Suematsu, Quoc Le, and Alex Kurakin · 2017
Closest in time.