A deep neural network compression algorithm based on knowledge transfer for edge devices
暂无分享,去创建一个
Weisong Shi | Luqi Gong | Chao Li | Yiwen Zhang | Yanming Chen | Xiang Wen | Weisong Shi | Chao-Lei Li | Yanming Chen | Xiang Wen | Yiwen Zhang | Luqi Gong
[1] Xuyun Zhang,et al. Data-Driven Web APIs Recommendation for Building Web Applications , 2022, IEEE Transactions on Big Data.
[2] Geoffrey E. Hinton,et al. Deep Learning , 2015, Nature.
[3] Weisong Shi,et al. The Promise of Edge Computing , 2016, Computer.
[4] Kilian Q. Weinberger,et al. Densely Connected Convolutional Networks , 2016, 2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).
[5] François Chollet,et al. Xception: Deep Learning with Depthwise Separable Convolutions , 2016, 2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).
[6] Jia Wang,et al. DaDianNao: A Machine-Learning Supercomputer , 2014, 2014 47th Annual IEEE/ACM International Symposium on Microarchitecture.
[7] Andrew Zisserman,et al. Very Deep Convolutional Networks for Large-Scale Image Recognition , 2014, ICLR.
[8] Zibin Zheng,et al. Covering-Based Web Service Quality Prediction via Neighborhood-Aware Matrix Factorization , 2019, IEEE Transactions on Services Computing.
[9] Joan Bruna,et al. Exploiting Linear Structure Within Convolutional Networks for Efficient Evaluation , 2014, NIPS.
[10] Song Han,et al. Learning both Weights and Connections for Efficient Neural Network , 2015, NIPS.
[11] Geoffrey E. Hinton,et al. Distilling the Knowledge in a Neural Network , 2015, ArXiv.
[12] Matti Pietikäinen,et al. Deep Learning for Generic Object Detection: A Survey , 2018, International Journal of Computer Vision.
[13] Haibin Zhu,et al. Location-Aware Deep Collaborative Filtering for Service Recommendation , 2021, IEEE Transactions on Systems, Man, and Cybernetics: Systems.
[14] Rich Caruana,et al. Do Deep Nets Really Need to be Deep? , 2013, NIPS.
[15] Zheng Zhang,et al. MXNet: A Flexible and Efficient Machine Learning Library for Heterogeneous Distributed Systems , 2015, ArXiv.
[16] Thomas G. Dietterich. Multiple Classifier Systems , 2000, Lecture Notes in Computer Science.
[17] Yoshua Bengio,et al. BinaryConnect: Training Deep Neural Networks with binary weights during propagations , 2015, NIPS.
[18] Dumitru Erhan,et al. Going deeper with convolutions , 2014, 2015 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).
[19] Huan Liu,et al. Neural-network feature selector , 1997, IEEE Trans. Neural Networks.
[20] Vineeth N. Balasubramanian,et al. Deep Model Compression: Distilling Knowledge from Noisy Teachers , 2016, ArXiv.
[21] Pascal Frossard,et al. Adaptive data augmentation for image classification , 2016, 2016 IEEE International Conference on Image Processing (ICIP).
[22] Jian Sun,et al. Deep Residual Learning for Image Recognition , 2015, 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).
[23] Shaoli Liu,et al. Cambricon: An Instruction Set Architecture for Neural Networks , 2016, 2016 ACM/IEEE 43rd Annual International Symposium on Computer Architecture (ISCA).
[24] Misha Denil,et al. Predicting Parameters in Deep Learning , 2014 .
[25] Rich Caruana,et al. Model compression , 2006, KDD '06.
[26] Huaming Wu,et al. Edge Server Quantification and Placement for Offloading Social Media Services in Industrial Cognitive IoV , 2021, IEEE Transactions on Industrial Informatics.
[27] Ming Yang,et al. Compressing Deep Convolutional Networks using Vector Quantization , 2014, ArXiv.
[28] Nitish Srivastava,et al. Dropout: a simple way to prevent neural networks from overfitting , 2014, J. Mach. Learn. Res..
[29] Yoshua Bengio,et al. FitNets: Hints for Thin Deep Nets , 2014, ICLR.
[30] Yonatan Belinkov,et al. Analysis Methods in Neural Language Processing: A Survey , 2018, TACL.
[31] Weisong Shi,et al. Edge Computing: Vision and Challenges , 2016, IEEE Internet of Things Journal.
[32] Geoffrey E. Hinton,et al. ImageNet classification with deep convolutional neural networks , 2012, Commun. ACM.
[33] Wanchun Dou,et al. Privacy-Aware Cross-Platform Service Recommendation Based on Enhanced Locality-Sensitive Hashing , 2021, IEEE Transactions on Network Science and Engineering.
[34] Yoram Singer,et al. Adaptive Subgradient Methods for Online Learning and Stochastic Optimization , 2011, J. Mach. Learn. Res..
[35] Song Han,et al. Deep Compression: Compressing Deep Neural Network with Pruning, Trained Quantization and Huffman Coding , 2015, ICLR.