深度学习深度信念网络DBNs—简易详解
2014-08-30 23:31
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针对实验室同门有些人向我问过DBNs,了解到,他们单单看论文,不能很好的理解DBNs,所有写了下面简易的图解;对一个初学深度神经网络的人,自己再结合理论证明,应该很容易理解这个模型。
参考文献:
[1]Hinton G E, Salakhutdinov R R. Reducing the dimensionality of data with neural networks. Science, vol. 313, pp. 504-507, 2006.
[2]Hinton G E, Osindero S, Teh Y W. A fast learning algorithm for deep belief nets. Neural computation, vol. 18, pp. 1527-1554, 2006.
[3]Xie, Jipeng, et al. "Learning features from High Speed Train vibration signals with Deep Belief Networks."
Neural Networks (IJCNN), 2014 International Joint Conference on. IEEE, 2014.
[4]Bengio Y, Lamblin P, Popovici D, et al. Greedy layer-wise training of deep networks. Advances in neural information processing systems, vol. 19, pp. 153-160, 2007.
[5]Salakhutdinov R. Learning deep generative models. Diss. University of Toronto, 2009.
[6]Hinton G. A practical guide to training restricted Boltzmann machines. Neural Networks: Tricks of the Trade, pp. 599-619, 2012.
[7]Bengio Y. Learning deep architectures for AI. Foundations and trends® in Machine Learning, vol. 2, pp. 1-127, 2009.
参考文献:
[1]Hinton G E, Salakhutdinov R R. Reducing the dimensionality of data with neural networks. Science, vol. 313, pp. 504-507, 2006.
[2]Hinton G E, Osindero S, Teh Y W. A fast learning algorithm for deep belief nets. Neural computation, vol. 18, pp. 1527-1554, 2006.
[3]Xie, Jipeng, et al. "Learning features from High Speed Train vibration signals with Deep Belief Networks."
Neural Networks (IJCNN), 2014 International Joint Conference on. IEEE, 2014.
[4]Bengio Y, Lamblin P, Popovici D, et al. Greedy layer-wise training of deep networks. Advances in neural information processing systems, vol. 19, pp. 153-160, 2007.
[5]Salakhutdinov R. Learning deep generative models. Diss. University of Toronto, 2009.
[6]Hinton G. A practical guide to training restricted Boltzmann machines. Neural Networks: Tricks of the Trade, pp. 599-619, 2012.
[7]Bengio Y. Learning deep architectures for AI. Foundations and trends® in Machine Learning, vol. 2, pp. 1-127, 2009.
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