Machine learning of inductive bias
Machine learning of inductive bias
CHILD: A First Step Towards Continual Learning
Machine Learning - Special issue on inductive transfer
Learning to learn
Explanation-Based Neural Network Learning: A Lifelong Learning Approach
Explanation-Based Neural Network Learning: A Lifelong Learning Approach
The Task Rehearsal Method of Life-Long Learning: Overcoming Impoverished Data
AI '02 Proceedings of the 15th Conference of the Canadian Society for Computational Studies of Intelligence on Advances in Artificial Intelligence
Inductive transfer with context-sensitive neural networks
Machine Learning
Adjusting bias in concept learning
IJCAI'83 Proceedings of the Eighth international joint conference on Artificial intelligence - Volume 1
Learning Deep Architectures for AI
Foundations and Trends® in Machine Learning
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We propose that it is appropriate to more seriously consider the nature of systems that are capable of learning over a lifetime. There are three reasons for taking this position. First, there exists a body of related work for this research under names such as constructive induction, continual learning, sequential task learning and most recently learning with deep architectures. Second, the computational and data storage power of modern computers are capable of implementing and testing machine lifelong learning systems. Third, there are significant challenges and benefits to pursuing programs of research in the area to AGI and brain sciences. This paper discusses each of the above in the context of a general framework for machine lifelong learning.