Low-Rank Approximations for Conditional Feedforward Computation in Deep
Neural Networks

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Low-Rank Approximations for Conditional Feedforward Computation in Deep Neural Networks

16 December 2013

Andrew S. Davis

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Papers citing "Low-Rank Approximations for Conditional Feedforward Computation in Deep Neural Networks"

8 / 8 papers shown

Title
Low-Rank Interconnected Adaptation across Layers Yibo Zhong Jinman Zhao Yao Zhou OffRL MoE 89 1 0 13 Jul 2024
Outrageously Large Neural Networks: The Sparsely-Gated Mixture-of-Experts Layer Noam M. Shazeer Azalia Mirhoseini Krzysztof Maziarz Andy Davis Quoc V. Le Geoffrey E. Hinton J. Dean MoE 251 2,683 0 23 Jan 2017
Estimating or Propagating Gradients Through Stochastic Neurons for Conditional Computation Yoshua Bengio Nicholas Léonard Aaron Courville 387 3,151 0 15 Aug 2013
Predicting Parameters in Deep Learning Misha Denil B. Shakibi Laurent Dinh MarcÁurelio Ranzato Nando de Freitas OOD 205 1,320 0 03 Jun 2013
Deep Learning of Representations: Looking Forward Yoshua Bengio 218 682 0 02 May 2013
Saturating Auto-Encoders Rostislav Goroshin Yann LeCun 72 43 0 16 Jan 2013
Improving neural networks by preventing co-adaptation of feature detectors Geoffrey E. Hinton Nitish Srivastava A. Krizhevsky Ilya Sutskever Ruslan Salakhutdinov VLM 457 7,666 0 03 Jul 2012
Building high-level features using large scale unsupervised learning Quoc V. Le MarcÁurelio Ranzato R. Monga M. Devin Kai Chen G. Corrado J. Dean A. Ng SSL OffRL CVBM 122 2,272 0 29 Dec 2011

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