- Author:
- Sebastian Thrun
From the Publisher:
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.
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- Wu X, Dai P, Deng W, Chen H, Wu Y, Cao Y, Shan Y and Qi X CL-NeRF Proceedings of the 37th International Conference on Neural Information Processing Systems, (34426-34438)
- Basu S, Kveton B, Zaheer M and Szepesvári C No regrets for learning the prior in bandits Proceedings of the 35th International Conference on Neural Information Processing Systems, (28029-28041)
- Wick J, Hemberg E and O’Reilly U Getting a Head Start on Program Synthesis with Genetic Programming Genetic Programming, (263-279)
- Boutilier C, Hsu C, Kveton B, Mladenov M, Szepesv�ri C and Zaheer M Differentiable meta-learning of bandit policies Proceedings of the 34th International Conference on Neural Information Processing Systems, (2122-2134)
- Sodhani S, Chandar S and Bengio Y (2020). Toward Training Recurrent Neural Networks for Lifelong Learning, Neural Computation, 32:1, (1-35), Online publication date: 1-Jan-2020.
- Stark S, Peters J and Rueckert E A comparison of distance measures for learning nonparametric motor skill libraries 2017 IEEE-RAS 17th International Conference on Humanoid Robotics (Humanoids), (624-630)
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