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Connection Science Volume 1, 1989 - Issue 4
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Original Articles

A Local Learning Algorithm for Dynamic Feedforward and Recurrent Networks

JURGEN SCHMIDHUBER Inscitut fur Informatik, Technische Universitat Munchen, Arcisstr. 21 Tel. 089-2105 2406, Munchen, 8000 E-mail: [email protected].
Pages 403-412 | Published online: 24 Oct 2007

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Vishwa S. Parekh & Michael A. Jacobs. (2019) Deep learning and radiomics in precision medicine. Expert Review of Precision Medicine and Drug Development 4:2, pages 59-72.
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Guangquan Lu, Xishun Zhao, Jian Yin, Weiwei Yang & Bo Li. (2020) Multi-task learning using variational auto-encoder for sentiment classification. Pattern Recognition Letters 132, pages 115-122.
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Alexandre Muzy & Bernard P. Zeigler. (2017) Activity-Based Credit Assignment Heuristic for Simulation-Based Stochastic Search in a Hierarchical Model Base of Systems. IEEE Systems Journal 11:4, pages 1916-1927.
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Truc Le, Giang Bui & Ye Duan. (2017) A multi-view recurrent neural network for 3D mesh segmentation. Computers & Graphics 66, pages 103-112.
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Wenjie Pei, Tadas Baltrusaitis, David M. J. Tax & Louis-Philippe Morency. (2017) Temporal Attention-Gated Model for Robust Sequence Classification. Temporal Attention-Gated Model for Robust Sequence Classification.
Jürgen Schmidhuber. 2017. Encyclopedia of Machine Learning and Data Mining. Encyclopedia of Machine Learning and Data Mining 338 348 .
Rui Zhao, Jinjiang Wang, Ruqiang Yan & Kezhi Mao. (2016) Machine health monitoring with LSTM networks. Machine health monitoring with LSTM networks.
Yangyang Lu, Ge Li, Rui Miao & Zhi Jin. 2016. Knowledge Science, Engineering and Management. Knowledge Science, Engineering and Management 527 539 .
Zhen Li, Yukang Gan, Xiaodan Liang, Yizhou Yu, Hui Cheng & Liang Lin. 2016. Computer Vision – ECCV 2016. Computer Vision – ECCV 2016 541 557 .
Jürgen Schmidhuber. 2016. Encyclopedia of Machine Learning and Data Mining. Encyclopedia of Machine Learning and Data Mining 1 11 .
Jungruyl Kim, Jaehyun Lee & Jeill Oh. (2015) Development of Wastewater Treatment Process Simulators Based on Artificial Neural Network and Mass Balance Models. Journal of the Korean Society of Water and Wastewater 29:3, pages 427-436.
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Jürgen Schmidhuber. (2015) Deep learning in neural networks: An overview. Neural Networks 61, pages 85-117.
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P. Szymczyk & M. Szymczyk. (2015) Classification of geological structure using ground penetrating radar and Laplace transform artificial neural networks. Neurocomputing 148, pages 354-362.
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Rupesh Kumar Srivastava, Bas R. Steunebrink & Jürgen Schmidhuber. (2013) First experiments with PowerPlay. Neural Networks 41, pages 130-136.
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Jürgen Schmidhuber. 2013. Intrinsically Motivated Learning in Natural and Artificial Systems. Intrinsically Motivated Learning in Natural and Artificial Systems 95 128 .
Rupesh Kumar Srivastava, Bas R. Steunebrink, Marijn Stollenga & Jurgen Schmidhuber. (2012) Continually adding self-invented problems to the repertoire: First experiments with POWERPLAY. Continually adding self-invented problems to the repertoire: First experiments with POWERPLAY.
Matthew Luciw & Juergen Schmidhuber. 2012. Artificial Neural Networks and Machine Learning – ICANN 2012. Artificial Neural Networks and Machine Learning – ICANN 2012 279 287 .
Ueli Rutishauser, Rodney J. Douglas & Jean-Jacques Slotine. (2011) Collective Stability of Networks of Winner-Take-All Circuits. Neural Computation 23:3, pages 735-773.
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Linus Gisslén, Matt Luciw, Vincent Graziano & Jürgen Schmidhuber. 2011. Artificial General Intelligence. Artificial General Intelligence 31 40 .
Jürgen Schmidhuber. (2010) Formal Theory of Creativity, Fun, and Intrinsic Motivation (1990–2010). IEEE Transactions on Autonomous Mental Development 2:3, pages 230-247.
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Juan Antonio Pérez-Ortiz, Felix A. Gers, Douglas Eck & Jürgen Schmidhuber. (2003) Kalman filters improve LSTM network performance in problems unsolvable by traditional recurrent nets. Neural Networks 16:2, pages 241-250.
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Jürgen Schmidhuber. 2003. Advances in Evolutionary Computing. Advances in Evolutionary Computing 579 612 .
F.A. Gers & E. Schmidhuber. (2001) LSTM recurrent networks learn simple context-free and context-sensitive languages. IEEE Transactions on Neural Networks 12:6, pages 1333-1340.
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Jean-Philippe Draye. 2001. Plausible Neural Networks for Biological Modelling. Plausible Neural Networks for Biological Modelling 49 74 .
Ivo Kwee, Marcus Hutter & Jürgen Schmidhuber. 2001. Artificial Neural Networks — ICANN 2001. Artificial Neural Networks — ICANN 2001 865 873 .
Felix A. Gers, Jürgen Schmidhuber & Fred Cummins. (2000) Learning to Forget: Continual Prediction with LSTM. Neural Computation 12:10, pages 2451-2471.
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Jürgen Schmidhuber. 2001. Sequence Learning. Sequence Learning 213 240 .
J. Schmidhuber. (1999) Artificial curiosity based on discovering novel algorithmic predictability through coevolution. Artificial curiosity based on discovering novel algorithmic predictability through coevolution.
Sepp Hochreiter & Jürgen Schmidhuber. (1997) Long Short-Term Memory. Neural Computation 9:8, pages 1735-1780.
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Jürgen Schmidhuber. (1997) Discovering Neural Nets with Low Kolmogorov Complexity and High Generalization Capability. Neural Networks 10:5, pages 857-873.
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J.-P.S. Draye, D.A. Pavisic, G.A. Cheron & G.A. Libert. (1996) Dynamic recurrent neural networks: a dynamical analysis. IEEE Transactions on Systems, Man, and Cybernetics, Part B (Cybernetics) 26:5, pages 692-706.
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Tibor Chovan, Thierry Catfolis & Kürt Meert. (1996) Neural network architecture for process control based on the RTRL algorithm. AIChE Journal 42:2, pages 493-502.
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Jürgen Schmidhuber. 1991. Connectionist Models. Connectionist Models 52 61 .
Oscar Claveria, Enric Monte & Salvador Torra. (2013) Tourism Demand Forecasting with Different Neural Networks Models. SSRN Electronic Journal.
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