ADA-Tucker: Compressing deep neural networks via adaptive dimension adjustment tucker decomposition
暂无分享,去创建一个
Chao Zhang | Zhouchen Lin | Zhisheng Zhong | Fangyin Wei | Zhouchen Lin | Chao Zhang | Fangyin Wei | Zhisheng Zhong
[1] Nikos Komodakis,et al. Wide Residual Networks , 2016, BMVC.
[2] Geoffrey E. Hinton,et al. Distilling the Knowledge in a Neural Network , 2015, ArXiv.
[3] Ivan V. Oseledets,et al. Speeding-up Convolutional Neural Networks Using Fine-tuned CP-Decomposition , 2014, ICLR.
[4] Joos Vandewalle,et al. On the Best Rank-1 and Rank-(R1 , R2, ... , RN) Approximation of Higher-Order Tensors , 2000, SIAM J. Matrix Anal. Appl..
[5] Geoffrey E. Hinton,et al. ImageNet classification with deep convolutional neural networks , 2012, Commun. ACM.
[6] Xiaogang Wang,et al. Convolutional neural networks with low-rank regularization , 2015, ICLR.
[7] Yoshua Bengio,et al. Gradient-based learning applied to document recognition , 1998, Proc. IEEE.
[8] Jianxin Wu,et al. ThiNet: A Filter Level Pruning Method for Deep Neural Network Compression , 2017, 2017 IEEE International Conference on Computer Vision (ICCV).
[9] Yoshua Bengio,et al. Understanding the difficulty of training deep feedforward neural networks , 2010, AISTATS.
[10] Yixin Chen,et al. Compressing Neural Networks with the Hashing Trick , 2015, ICML.
[11] Rich Caruana,et al. Do Deep Nets Really Need to be Deep? , 2013, NIPS.
[12] Alexander Novikov,et al. Tensorizing Neural Networks , 2015, NIPS.
[13] Dumitru Erhan,et al. Going deeper with convolutions , 2014, 2015 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).
[14] Jingdong Wang,et al. Interleaved Group Convolutions , 2017, 2017 IEEE International Conference on Computer Vision (ICCV).
[15] Ming Yang,et al. Compressing Deep Convolutional Networks using Vector Quantization , 2014, ArXiv.
[16] Yixin Chen,et al. Compressing Convolutional Neural Networks in the Frequency Domain , 2016, KDD.
[17] Kilian Q. Weinberger,et al. Densely Connected Convolutional Networks , 2016, 2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).
[18] Tamara G. Kolda,et al. Tensor Decompositions and Applications , 2009, SIAM Rev..
[19] Yoshua Bengio,et al. BinaryConnect: Training Deep Neural Networks with binary weights during propagations , 2015, NIPS.
[20] Song Han,et al. Deep Compression: Compressing Deep Neural Network with Pruning, Trained Quantization and Huffman Coding , 2015, ICLR.
[21] Max Welling,et al. Soft Weight-Sharing for Neural Network Compression , 2017, ICLR.
[22] Misha Denil,et al. Predicting Parameters in Deep Learning , 2014 .
[23] Zhouchen Lin,et al. Convolutional Neural Networks with Alternately Updated Clique , 2018, 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition.
[24] Kai Yu,et al. Very deep convolutional neural networks for LVCSR , 2015, INTERSPEECH.
[25] V. Lempitsky,et al. Speeding-up convolutional neural networks: A survey , 2023, Bulletin of the Polish Academy of Sciences Technical Sciences.
[26] Song Han,et al. Learning both Weights and Connections for Efficient Neural Network , 2015, NIPS.
[27] Zhuowen Tu,et al. Aggregated Residual Transformations for Deep Neural Networks , 2016, 2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).
[28] Andrew Zisserman,et al. Speeding up Convolutional Neural Networks with Low Rank Expansions , 2014, BMVC.
[29] Andrew Zisserman,et al. Very Deep Convolutional Networks for Large-Scale Image Recognition , 2014, ICLR.
[30] Joan Bruna,et al. Exploiting Linear Structure Within Convolutional Networks for Efficient Evaluation , 2014, NIPS.
[31] Jian Sun,et al. Delving Deep into Rectifiers: Surpassing Human-Level Performance on ImageNet Classification , 2015, 2015 IEEE International Conference on Computer Vision (ICCV).
[32] Yurong Chen,et al. Dynamic Network Surgery for Efficient DNNs , 2016, NIPS.
[33] Jimmy Ba,et al. Adam: A Method for Stochastic Optimization , 2014, ICLR.
[34] Lin Xu,et al. Incremental Network Quantization: Towards Lossless CNNs with Low-Precision Weights , 2017, ICLR.
[35] Dacheng Tao,et al. Packing Convolutional Neural Networks in the Frequency Domain , 2016, IEEE Transactions on Pattern Analysis and Machine Intelligence.
[36] Eunhyeok Park,et al. Compression of Deep Convolutional Neural Networks for Fast and Low Power Mobile Applications , 2015, ICLR.
[37] Jian Sun,et al. Deep Residual Learning for Image Recognition , 2015, 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).