Lifelong learning addresses situations in which a learner faces a series of different learning tasks providing the opportunity for synergy among them. Explanation-based neural network learning (EBNN) is a machine learning algorithm that transfers knowledge across multiple learning tasks. When faced with a new learning task, EBNN exploits domain knowledge accumulated in previous learning tasks to guide generalization in the new one. As a result, EBNN generalizes more accurately from less data than comparable methods. Explanation-Based Neural Network Learning: A Lifelong Learning Approach describes the basic EBNN paradigm and investigates it in the context of supervised learning, reinforcement learning, robotics, and chess. `The paradigm of lifelong learning – using earlier learned knowledge to improve subsequent learning – is a promising direction for a new generation of machine learning algorithms. Given the need for more accurate learning methods, it is difficult to imagine a future for machine learning that does not include this paradigm.’ From the Foreword by Tom M. Mitchell.
Sebastian Thrun
Explanation-Based Neural Network Learning [PDF ebook]
A Lifelong Learning Approach
Explanation-Based Neural Network Learning [PDF ebook]
A Lifelong Learning Approach
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语言 英语 ● 格式 PDF ● ISBN 9781461313816 ● 出版者 Springer US ● 发布时间 2012 ● 下载 3 时 ● 货币 EUR ● ID 4599852 ● 复制保护 Adobe DRM
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