Regularization of Neural Networks using DropConnect
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Yann LeCun | Li Wan | Rob Fergus | Matthew D. Zeiler | Sixin Zhang | R. Fergus | Yann LeCun | Sixin Zhang | Li Wan
[1] J. Kuelbs. Probability on Banach spaces , 1978 .
[2] David E. Rumelhart,et al. Generalization by Weight-Elimination with Application to Forecasting , 1990, NIPS.
[3] David Mackay,et al. Probable networks and plausible predictions - a review of practical Bayesian methods for supervised neural networks , 1995 .
[4] Yoshua Bengio,et al. Gradient-based learning applied to document recognition , 1998, Proc. IEEE.
[5] V. Koltchinskii,et al. Empirical margin distributions and bounding the generalization error of combined classifiers , 2002, math/0405343.
[6] Y. LeCun,et al. Learning methods for generic object recognition with invariance to pose and lighting , 2004, Proceedings of the 2004 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, 2004. CVPR 2004..
[7] Alex Krizhevsky,et al. Learning Multiple Layers of Features from Tiny Images , 2009 .
[8] Geoffrey E. Hinton,et al. Rectified Linear Units Improve Restricted Boltzmann Machines , 2010, ICML.
[9] Andrew Y. Ng,et al. Reading Digits in Natural Images with Unsupervised Feature Learning , 2011 .
[10] Nitish Srivastava,et al. Improving neural networks by preventing co-adaptation of feature detectors , 2012, ArXiv.
[11] Jasper Snoek,et al. Practical Bayesian Optimization of Machine Learning Algorithms , 2012, NIPS.
[12] Jürgen Schmidhuber,et al. Multi-column deep neural networks for image classification , 2012, 2012 IEEE Conference on Computer Vision and Pattern Recognition.
[13] Rob Fergus,et al. Stochastic Pooling for Regularization of Deep Convolutional Neural Networks , 2013, ICLR.