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Learning to solve complex sequences of tasks--while both leveraging transfer and avoiding catastrophic forgetting--remains a key obstacle to achieving human-level intelligence.
The cascade-correlation learning architecture
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Optimal brain damage
Yann LeCun, John S. Denker, and Sara A. Solla · 1990
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Continual Learning in Reinforcement Environments
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Natural gradient works efficiently in learning
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Reducing the dimensionality of data with neural networks
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An introduction to inter-task transfer for reinforcement learning
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Deep learning of representations for unsupervised and transfer learning
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Multi-column deep neural networks for image classification
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Unsupervised and transfer learning challenge: a deep learning approach
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Human-level control through deep reinforcement learning
V. Mnih, Kk Kavukcuoglu, D. Silver, A. Rusu, J. Veness, M. Bellemare, A. Graves, M. Riedmiller, A. Fidjeland, G. Ostrovski, S. Petersen, C. Beattie, A. Sadik, I. Antonoglou, H. King, D. Kumaran, D. Wierstra, S. Legg, and D. Hassabis · 2015
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Knowledge Transfer in Deep Block-Modular Neural Networks
Alexander V. Terekhov, Guglielmo Montone, and J. Kevin O’Regan · 2015
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Asynchronous methods for deep reinforcement learning
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