Explanation-Based Neural Network Learning : a Lifelong Learning Approach /
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...
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| Format: | eBook |
| Language: | English |
| Published: |
Boston, MA :
Springer US,
1996.
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| Series: | Kluwer international series in engineering and computer science. Knowledge representation, learning, and expert systems ;
357. |
| Subjects: | |
| Online Access: | Connect to the full text of this electronic book |
| Summary: | 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. |
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| Item Description: | Electronic resource. |
| Physical Description: | 1 online resource (280 pages) |
| ISBN: | 9781461313816 (electronic bk.) 1461313813 (electronic bk.) |
| ISSN: | 0893-3405 ; |