Recurrent neural network training with dark knowledge transfer
暂无分享,去创建一个
[1] Geoffrey E. Hinton,et al. Distilling the Knowledge in a Neural Network , 2015, ArXiv.
[2] Geoffrey E. Hinton,et al. On the importance of initialization and momentum in deep learning , 2013, ICML.
[3] Rich Caruana,et al. Do Deep Nets Really Need to be Deep? , 2013, NIPS.
[4] Harald Haas,et al. Harnessing Nonlinearity: Predicting Chaotic Systems and Saving Energy in Wireless Communication , 2004, Science.
[5] Biing-Hwang Juang,et al. Recurrent deep neural networks for robust speech recognition , 2014, 2014 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP).
[6] Li Deng,et al. A tutorial survey of architectures, algorithms, and applications for deep learning , 2014, APSIPA Transactions on Signal and Information Processing.
[7] Daniel Povey,et al. The Kaldi Speech Recognition Toolkit , 2011 .
[8] Geoffrey E. Hinton,et al. Learning representations by back-propagating errors , 1986, Nature.
[9] Tara N. Sainath,et al. FUNDAMENTAL TECHNOLOGIES IN MODERN SPEECH RECOGNITION Digital Object Identifier 10.1109/MSP.2012.2205597 , 2012 .
[10] Yifan Gong,et al. Learning small-size DNN with output-distribution-based criteria , 2014, INTERSPEECH.
[11] Yoshua Bengio,et al. FitNets: Hints for Thin Deep Nets , 2014, ICLR.
[12] William Chan,et al. Transferring knowledge from a RNN to a DNN , 2015, INTERSPEECH.
[13] James Martens,et al. Deep learning via Hessian-free optimization , 2010, ICML.
[14] Yoshua Bengio,et al. Greedy Layer-Wise Training of Deep Networks , 2006, NIPS.
[15] Yoshua Bengio,et al. Why Does Unsupervised Pre-training Help Deep Learning? , 2010, AISTATS.
[16] Andrew W. Senior,et al. Long short-term memory recurrent neural network architectures for large scale acoustic modeling , 2014, INTERSPEECH.
[17] Rich Caruana,et al. Model compression , 2006, KDD '06.
[18] Jürgen Schmidhuber,et al. Long Short-Term Memory , 1997, Neural Computation.
[19] Ilya Sutskever,et al. Learning Recurrent Neural Networks with Hessian-Free Optimization , 2011, ICML.
[20] Dong Yu,et al. Deep Learning: Methods and Applications , 2014, Found. Trends Signal Process..
[21] Geoffrey E. Hinton,et al. Speech recognition with deep recurrent neural networks , 2013, 2013 IEEE International Conference on Acoustics, Speech and Signal Processing.
[22] Dong Yu,et al. Large vocabulary continuous speech recognition with context-dependent DBN-HMMS , 2011, 2011 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP).
[23] Jürgen Schmidhuber,et al. Deep learning in neural networks: An overview , 2014, Neural Networks.
[24] Yoshua Bengio,et al. Learning long-term dependencies with gradient descent is difficult , 1994, IEEE Trans. Neural Networks.
[25] Geoffrey E. Hinton,et al. Reducing the Dimensionality of Data with Neural Networks , 2006, Science.
[26] Navdeep Jaitly,et al. Towards End-To-End Speech Recognition with Recurrent Neural Networks , 2014, ICML.
[27] Dong Yu,et al. Context-Dependent Pre-Trained Deep Neural Networks for Large-Vocabulary Speech Recognition , 2012, IEEE Transactions on Audio, Speech, and Language Processing.
[28] Jürgen Schmidhuber,et al. Framewise phoneme classification with bidirectional LSTM and other neural network architectures , 2005, Neural Networks.
[29] Björn W. Schuller,et al. Robust speech recognition using long short-term memory recurrent neural networks for hybrid acoustic modelling , 2014, INTERSPEECH.