Variational Student: Learning Compact and Sparser Networks in Knowledge
Distillation Framework

Variational Student: Learning Compact and Sparser Networks in Knowledge Distillation Framework

26 October 2019

Ranjitha Prasad

R. Hebbalaguppe

Vishwajith Kumar

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Papers citing "Variational Student: Learning Compact and Sparser Networks in Knowledge Distillation Framework"

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Title
Variational Bayesian dropout: pitfalls and fixes Jiri Hron A. G. Matthews Zoubin Ghahramani BDL 93 67 0 05 Jul 2018
Learning Intrinsic Sparse Structures within Long Short-Term Memory W. Wen Yuxiong He Samyam Rajbhandari Minjia Zhang Wenhan Wang Fang Liu Bin Hu Yiran Chen H. Li MQ 118 142 0 15 Sep 2017
Bayesian Compression for Deep Learning Christos Louizos Karen Ullrich Max Welling UQCV BDL 195 481 0 24 May 2017
Variational Dropout Sparsifies Deep Neural Networks Dmitry Molchanov Arsenii Ashukha Dmitry Vetrov BDL 176 831 0 19 Jan 2017
Learning Structured Sparsity in Deep Neural Networks W. Wen Chunpeng Wu Yandan Wang Yiran Chen Hai Helen Li 189 2,341 0 12 Aug 2016
Deep Compression: Compressing Deep Neural Networks with Pruning, Trained Quantization and Huffman Coding Song Han Huizi Mao W. Dally 3DGS 263 8,862 0 01 Oct 2015
Learning both Weights and Connections for Efficient Neural Networks Song Han Jeff Pool J. Tran W. Dally CVBM 316 6,709 0 08 Jun 2015
Variational Dropout and the Local Reparameterization Trick Diederik P. Kingma Tim Salimans Max Welling BDL 229 1,517 0 08 Jun 2015
FitNets: Hints for Thin Deep Nets Adriana Romero Nicolas Ballas Samira Ebrahimi Kahou Antoine Chassang C. Gatta Yoshua Bengio FedML 322 3,906 0 19 Dec 2014
Exploiting Linear Structure Within Convolutional Networks for Efficient Evaluation Emily L. Denton Wojciech Zaremba Joan Bruna Yann LeCun Rob Fergus FAtt 179 1,693 0 02 Apr 2014
Do Deep Nets Really Need to be Deep? Lei Jimmy Ba R. Caruana 188 2,120 0 21 Dec 2013