Deep Compression: Compressing Deep Neural Network with Pruning, Trained …

Articles citing Deep Compression: Compressing Deep Neural Network with Pruning, Trained …

Title / Author	Year
Mobilenets: Efficient convolutional neural networks for mobile vision applications AG Howard, M Zhu, B Chen, D Kalenichenko, W Wang, T Weyand, ... arXiv preprint arXiv:1704.04861	2017
Google's neural machine translation system: Bridging the gap between human and machine translation Y Wu, M Schuster, Z Chen, QV Le, M Norouzi, W Macherey, M Krikun, ... arXiv preprint arXiv:1609.08144	2016
SqueezeNet: AlexNet-level accuracy with 50x fewer parameters and< 0.5 MB model size FN Iandola, S Han, MW Moskewicz, K Ashraf, WJ Dally, K Keutzer arXiv preprint arXiv:1602.07360	2016
Learning both weights and connections for efficient neural network S Han, J Pool, J Tran, W Dally Advances in neural information processing systems, 1135-1143	2015
Xnor-net: Imagenet classification using binary convolutional neural networks M Rastegari, V Ordonez, J Redmon, A Farhadi European conference on computer vision, 525-542	2016
Shufflenet: An extremely efficient convolutional neural network for mobile devices X Zhang, X Zhou, M Lin, J Sun Proceedings of the IEEE conference on computer vision and pattern …	2018
EIE: efficient inference engine on compressed deep neural network S Han, X Liu, H Mao, J Pu, A Pedram, MA Horowitz, WJ Dally ACM SIGARCH Computer Architecture News 44 (3), 243-254	2016
Pruning filters for efficient convnets H Li, A Kadav, I Durdanovic, H Samet, HP Graf arXiv preprint arXiv:1608.08710	2016
Recent advances in convolutional neural networks J Gu, Z Wang, J Kuen, L Ma, A Shahroudy, B Shuai, T Liu, X Wang, ... Pattern Recognition 77, 354-377	2018
Efficient processing of deep neural networks: A tutorial and survey V Sze, YH Chen, TJ Yang, JS Emer Proceedings of the IEEE 105 (12), 2295-2329	2017
Learning structured sparsity in deep neural networks W Wen, C Wu, Y Wang, Y Chen, H Li Advances in neural information processing systems, 2074-2082	2016
Sgdr: Stochastic gradient descent with warm restarts I Loshchilov, F Hutter arXiv preprint arXiv:1608.03983	2016
Binarized neural networks I Hubara, M Courbariaux, D Soudry, R El-Yaniv, Y Bengio Advances in neural information processing systems, 4107-4115	2016
Dorefa-net: Training low bitwidth convolutional neural networks with low bitwidth gradients S Zhou, Y Wu, Z Ni, X Zhou, H Wen, Y Zou arXiv preprint arXiv:1606.06160	2016
Quantized neural networks: Training neural networks with low precision weights and activations I Hubara, M Courbariaux, D Soudry, R El-Yaniv, Y Bengio The Journal of Machine Learning Research 18 (1), 6869-6898	2017
Enet: A deep neural network architecture for real-time semantic segmentation A Paszke, A Chaurasia, S Kim, E Culurciello arXiv preprint arXiv:1606.02147	2016
Channel pruning for accelerating very deep neural networks Y He, X Zhang, J Sun Proceedings of the IEEE International Conference on Computer Vision, 1389-1397	2017
Eyeriss: A spatial architecture for energy-efficient dataflow for convolutional neural networks YH Chen, J Emer, V Sze ACM SIGARCH Computer Architecture News 44 (3), 367-379	2016
Image super-resolution via deep recursive residual network Y Tai, J Yang, X Liu Proceedings of the IEEE conference on computer vision and pattern …	2017
Federated learning: Strategies for improving communication efficiency J Konečný, HB McMahan, FX Yu, P Richtárik, AT Suresh, D Bacon arXiv preprint arXiv:1610.05492	2016

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