Jürgen Schmidhuber
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Jürgen Schmidhuber is a person.
- See: LSTM Network, Recurrent Network, IDSIA.
References
- Professional Homepage: http://people.idsia.ch/~juergen/
- Google Scholar Author Page: http://scholar.google.com/citations?user=gLnCTgIAAAAJ
2017
- (Schmidhuber, 2017) ⇒ Jürgen Schmidhuber (2017) "Deep Learning". In: Sammut, C., Webb, G.I. (eds) "Encyclopedia of Machine Learning and Data Mining". Springer, Boston, MA
- (Zilly et al., 2017) ⇒ Julian Georg Zilly, Rupesh Kumar Srivastava, Jan Koutník, and Jürgen Schmidhuber. (2017). “Recurrent Highway Networks.” In: Proceedings of the 34th International Conference on Machine Learning - Volume 70. arXiv:1607.03474
2015
- (Schmidhuber, 2015) ⇒ Jürgen Schmidhuber. (2015). “Deep Learning in Neural Networks: An Overview.” In: Neural Networks, 61.
- (Wikipedia, 2015) ⇒ http://en.wikipedia.org/wiki/Jürgen_Schmidhuber Retrieved:2015-1-10.
- Jürgen Schmidhuber (born 17 January 1963 in Munich) is a computer scientist and artist known for his work on machine learning, Artificial Intelligence (AI), artificial neural networks, digital physics, and low-complexity art. His contributions also include generalizations of Kolmogorov complexity and the Speed Prior. From 2004 to 2009 he was professor of Cognitive Robotics at the Tech. University Munich. Since 1995 he has been co-director of the Swiss AI Lab IDSIA in Lugano, since 2009 also professor of Artificial Intelligence at the University of Lugano. Between 2009 and 2012, the recurrent neural networks and deep feedforward neural networks developed in his research group have won eight international competitions in pattern recognition and machine learning. [1] In honor of his achievements he was elected to the European Academy of Sciences and Arts in 2008.
- ↑ 2012 Kurzweil AI Interview with Jürgen Schmidhuber on the eight competitions won by his Deep Learning team 2009-2012
2012
- (Schmidhuber, 2012) ⇒ Jürgen Schmidhuber. (2012). “Philosophers & futurists, catch up!.” In: Journal of Consciousness Studies, 19.
2011
- (Schmidhuber et al., 2011) ⇒ Jürgen Schmidhuber, Dan Ciresan, Ueli Meier, Jonathan Masci, and Alex Graves. (2011). “On Fast Deep Nets for AGI Vision.” In: Proceedings of the 4th International Conference on Artificial General Intelligence.
- (Masci et al., 2011) ⇒ Jonathan Masci, Ueli Meier, Dan Cireşan, and Jürgen Schmidhuber. (2011). “Stacked Convolutional Auto-encoders for Hierarchical Feature Extraction.” In: International conference on artificial neural networks.
2005
- (Graves & Schmidhuber, 2005) ⇒ Alex Graves, and Jürgen Schmidhuber. (2005). “Framewise Phoneme Classification with Bidirectional LSTM and Other Neural Network Architectures.” In: Neural Networks Journal, 18(5-6). doi:10.1016/j.neunet.2005.06.042
- (Graves, Fernandez & Schmidhuber, 2005) ⇒ Alex Graves, Santiago Fernandez, Jurgen Schmidhuber (2005, September). "Bidirectional LSTM networks for improved phoneme classification and recognition" (PDF). In: Proceedings of the International Conference on Artificial Neural Networks (pp. 799-804). Springer, Berlin, Heidelberg. DOI:10.1007/11550907_126
2001
- (Hochreiter et al., 2001) ⇒ Sepp Hochreiter, Yoshua Bengio, Paolo Frasconi, and Jürgen Schmidhuber. (2001). “Gradient Flow in Recurrent Nets: The Difficulty of Learning Long-term Dependencies.”
2000
- (Gers et al., 2000) ⇒ Felix A. Gers, Jürgen Schmidhuber, and Fred Cummins. (2000). “Learning to Forget: Continual Prediction with LSTM.” Neural Computation 12, no. 10
1997
- (Hochreiter & Schmidhuber, 1997) ⇒ Sepp Hochreiter, and Jürgen Schmidhuber. (1997). “Long Short-term Memory.” In: Neural computation, 9(8).
1994
- (Schmidhuber, 1994) ⇒ Jürgen Schmidhuber. (1994). “On Learning how to Learn Learning Strategies." Technical Report FKI-198-94, Fakultat Fur Informatik.
1991
- (Schmidhuber, 1994) ⇒ Jürgen Schmidhuber. (1991). “Curious model-building control systems." In Neural Networks, 1991. 1991 IEEE International Joint Conference on, pp. 1458-1463. IEEE, .