Learning to Adapt by Minimizing Discrepancy

30 November 2017

Papers citing "Learning to Adapt by Minimizing Discrepancy"

30 / 30 papers shown

Title
Learning Simpler Language Models with the Differential State Framework Alexander Ororbia Tomas Mikolov David Reitter AI4TS 47 65 0 26 Mar 2017
Unbiased Online Recurrent Optimization Corentin Tallec Yann Ollivier 83 99 0 16 Feb 2017
Training Language Models Using Target-Propagation Sam Wiseman S. Chopra MarcÁurelio Ranzato Arthur Szlam Ruoyu Sun Soumith Chintala Nicolas Vasilache 46 8 0 15 Feb 2017
Neuromorphic Deep Learning Machines Emre Neftci C. Augustine Somnath Paul Georgios Detorakis BDL 173 260 0 16 Dec 2016
Learning in the Machine: Random Backpropagation and the Deep Learning Channel Pierre Baldi Peter Sadowski Zhiqin Lu AAML 60 16 0 08 Dec 2016
A Modular Theory of Feature Learning D. McNamara Cheng Soon Ong Robert C. Williamson OOD SSL 41 4 0 09 Nov 2016
Exploiting Spatio-Temporal Structure with Recurrent Winner-Take-All Networks Eder Santana Matthew S. Emigh Pablo Zegers José C. Príncipe BDL 86 15 0 31 Oct 2016
Direct Feedback Alignment Provides Learning in Deep Neural Networks Arild Nøkland ODL 97 459 0 06 Sep 2016
Decoupled Neural Interfaces using Synthetic Gradients Max Jaderberg Wojciech M. Czarnecki Simon Osindero Oriol Vinyals Alex Graves David Silver Koray Kavukcuoglu 85 358 0 18 Aug 2016
Deep Predictive Coding Networks for Video Prediction and Unsupervised Learning William Lotter Gabriel Kreiman David D. Cox SSL 110 936 0 25 May 2016
Equilibrium Propagation: Bridging the Gap Between Energy-Based Models and Backpropagation B. Scellier Yoshua Bengio 68 494 0 16 Feb 2016
Online Semi-Supervised Learning with Deep Hybrid Boltzmann Machines and Denoising Autoencoders Alexander Ororbia C. Lee Giles David Reitter AI4CE 62 30 0 22 Nov 2015
How Important is Weight Symmetry in Backpropagation? Q. Liao Joel Z Leibo T. Poggio 73 170 0 17 Oct 2015
Deep Temporal Sigmoid Belief Networks for Sequence Modeling Zhe Gan Chunyuan Li Ricardo Henao David Carlson Lawrence Carin BDL 65 85 0 23 Sep 2015
A Theory of Feature Learning Brendan van Rooyen Robert C. Williamson OOD SSL FAtt 43 7 0 01 Apr 2015
Towards Biologically Plausible Deep Learning Yoshua Bengio Dong-Hyun Lee J. Bornschein Thomas Mesnard Zhouhan Lin DRL OOD 82 352 0 14 Feb 2015
Difference Target Propagation Dong-Hyun Lee Saizheng Zhang Asja Fischer Yoshua Bengio AAML 114 352 0 23 Dec 2014
Adam: A Method for Stochastic Optimization Diederik P. Kingma Jimmy Ba ODL 2.0K 150,312 0 22 Dec 2014
Random feedback weights support learning in deep neural networks Timothy Lillicrap D. Cownden D. Tweed C. Akerman ODL 72 171 0 02 Nov 2014
Deeply-Supervised Nets Chen-Yu Lee Saining Xie Patrick W. Gallagher Zhengyou Zhang Zhuowen Tu 350 2,243 0 18 Sep 2014
Reweighted Wake-Sleep J. Bornschein Yoshua Bengio BDL 109 183 0 11 Jun 2014
Neural Variational Inference and Learning in Belief Networks A. Mnih Karol Gregor BDL 189 729 0 31 Jan 2014
Intriguing properties of neural networks Christian Szegedy Wojciech Zaremba Ilya Sutskever Joan Bruna D. Erhan Ian Goodfellow Rob Fergus AAML 282 14,963 1 21 Dec 2013
Auto-Encoding Variational Bayes Diederik P. Kingma Max Welling BDL 455 16,923 0 20 Dec 2013
Deep Learning of Representations: Looking Forward Yoshua Bengio 218 682 0 02 May 2013
Deep Predictive Coding Networks R. Chalasani José C. Príncipe BDL 162 70 0 16 Jan 2013
On the difficulty of training Recurrent Neural Networks Razvan Pascanu Tomas Mikolov Yoshua Bengio ODL 204 5,360 0 21 Nov 2012
Modeling Temporal Dependencies in High-Dimensional Sequences: Application to Polyphonic Music Generation and Transcription Nicolas Boulanger-Lewandowski Yoshua Bengio Pascal Vincent 179 704 0 27 Jun 2012
Spike-and-Slab Sparse Coding for Unsupervised Feature Discovery Ian Goodfellow Aaron Courville Yoshua Bengio 78 61 0 16 Jan 2012
Fast Inference in Sparse Coding Algorithms with Applications to Object Recognition Koray Kavukcuoglu MarcÁurelio Ranzato Yann LeCun 110 247 0 18 Oct 2010