• Title Deep Learning in Neural Networks: An Overview
• Author(s) Juergen Schmidhuber
• Publisher: arxiv.org and University of Lugano; eBook (Creative Commons Licensed)
• License(s): Creative Commons License (CC)
• Hardcover N/A
• eBook PDF (206 pages)
• Language: English
• ISBN-10: N/A
• ISBN-13: N/A
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Book Description

In recent years, deep artificial neural networks (including recurrent ones) have won numerous contests in pattern recognition and machine learning. This historical survey compactly summarises 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. It reviews 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.

• Juergen Schmidhuber is a computer scientist most noted for his work in the field of artificial intelligence, deep learning and artificial neural networks.

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• Neural Networks
• Deep Learning
• Machine Learning
• Artificial Intelligence

• Deep Learning in Neural Networks: An Overview (Juergen Schmidhuber)
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