期刊
NEURAL NETWORKS
卷 61, 期 -, 页码 85-117出版社
PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.neunet.2014.09.003
关键词
Deep learning; Supervised learning; Unsupervised learning; Reinforcement learning; Evolutionary computation
资金
- SNF
- DFG
- European Commission
In recent years, deep artificial neural networks (including recurrent ones) have won numerous contests in pattern recognition and machine learning. This historical survey compactly summarizes relevant work, much of it from the previous millennium. Shallow and Deep Learners are distinguished by the depth of their credit assignment paths, which are chains of possibly learnable, causal links between actions and effects. I review deep supervised learning (also recapitulating the history of backpropagation), unsupervised learning, reinforcement learning & evolutionary computation, and indirect search for short programs encoding deep and large networks. (C) 2014 Published by Elsevier Ltd.
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