Tensor Contraction Layers for Parsimonious Deep Nets
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Anima Anandkumar | Jean Kossaifi | Tommaso Furlanello | Aran Khanna | Zachary Chase Lipton | Anima Anandkumar | Tommaso Furlanello | Jean Kossaifi | A. Khanna | Aran Khanna
[1] Andrew Zisserman,et al. Very Deep Convolutional Networks for Large-Scale Image Recognition , 2014, ICLR.
[2] Eunhyeok Park,et al. Compression of Deep Convolutional Neural Networks for Fast and Low Power Mobile Applications , 2015, ICLR.
[3] Tamara G. Kolda,et al. Tensor Decompositions and Applications , 2009, SIAM Rev..
[4] Anima Anandkumar,et al. Tensor decompositions for learning latent variable models , 2012, J. Mach. Learn. Res..
[5] Shuicheng Yan,et al. Sharing Residual Units Through Collective Tensor Factorization To Improve Deep Neural Networks , 2018, IJCAI.
[6] Nuria Oliver,et al. Multiverse recommendation: n-dimensional tensor factorization for context-aware collaborative filtering , 2010, RecSys '10.
[7] Ivan V. Oseledets,et al. Speeding-up Convolutional Neural Networks Using Fine-tuned CP-Decomposition , 2014, ICLR.
[8] Anima Anandkumar,et al. Generalization Bounds for Neural Networks through Tensor Factorization , 2015, ArXiv.
[9] Alexander Novikov,et al. Tensorizing Neural Networks , 2015, NIPS.
[10] Song Han,et al. Deep Compression: Compressing Deep Neural Network with Pruning, Trained Quantization and Huffman Coding , 2015, ICLR.
[11] Sergey Ioffe,et al. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift , 2015, ICML.
[12] René Vidal,et al. Global Optimality in Tensor Factorization, Deep Learning, and Beyond , 2015, ArXiv.
[13] Chen Yunpeng,et al. Sharing Residual Units Through Collective Tensor Factorization in Deep Neural Networks , 2017, ArXiv.
[14] Zheng Zhang,et al. MXNet: A Flexible and Efficient Machine Learning Library for Heterogeneous Distributed Systems , 2015, ArXiv.
[15] U. N. Niranjan,et al. Tensor Contractions with Extended BLAS Kernels on CPU and GPU , 2016, HiPC 2016.
[16] M. Irani. Vision Day Schedule Time Speaker and Collaborators Affiliation Title a General Preprocessing Method for Improved Performance of Epipolar Geometry Estimation Algorithms on the Expressive Power of Deep Learning: a Tensor Analysis , 2016 .
[17] Geoffrey E. Hinton,et al. ImageNet classification with deep convolutional neural networks , 2012, Commun. ACM.
[18] Yongxin Yang,et al. Deep Multi-task Representation Learning: A Tensor Factorisation Approach , 2016, ICLR.
[19] Alex Krizhevsky,et al. Learning Multiple Layers of Features from Tiny Images , 2009 .
[20] Anima Anandkumar,et al. Training Input-Output Recurrent Neural Networks through Spectral Methods , 2016, ArXiv.
[21] Fei-Fei Li,et al. ImageNet: A large-scale hierarchical image database , 2009, 2009 IEEE Conference on Computer Vision and Pattern Recognition.