Improving Performance on Problems with Few Labelled Data by Reusing Stacked Auto-Encoders
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Luís A. Alexandre | Joaquim Marques de Sá | Telmo Amaral | Luís M. Silva | Jorge M. Santos | Chetak Kandaswamy
[1] Yoshua. Bengio,et al. Learning Deep Architectures for AI , 2007, Found. Trends Mach. Learn..
[2] Yoshua Bengio,et al. Domain Adaptation for Large-Scale Sentiment Classification: A Deep Learning Approach , 2011, ICML.
[3] Dong Yu,et al. Deep Learning for Signal and Information Processing , 2013 .
[4] Georg Heigold,et al. Multilingual acoustic models using distributed deep neural networks , 2013, 2013 IEEE International Conference on Acoustics, Speech and Signal Processing.
[5] Pascal Vincent,et al. Representation Learning: A Review and New Perspectives , 2012, IEEE Transactions on Pattern Analysis and Machine Intelligence.
[6] Yoshua Bengio,et al. An empirical evaluation of deep architectures on problems with many factors of variation , 2007, ICML '07.
[7] Lorenzo Bruzzone,et al. Domain Adaptation Problems: A DASVM Classification Technique and a Circular Validation Strategy , 2010, IEEE Transactions on Pattern Analysis and Machine Intelligence.
[8] Jürgen Schmidhuber,et al. Transfer learning for Latin and Chinese characters with Deep Neural Networks , 2012, The 2012 International Joint Conference on Neural Networks (IJCNN).
[9] Yee Whye Teh,et al. A Fast Learning Algorithm for Deep Belief Nets , 2006, Neural Computation.
[10] Qiang Yang,et al. A Survey on Transfer Learning , 2010, IEEE Transactions on Knowledge and Data Engineering.
[11] Yifan Gong,et al. Cross-language knowledge transfer using multilingual deep neural network with shared hidden layers , 2013, 2013 IEEE International Conference on Acoustics, Speech and Signal Processing.