On-line Metalearning in Changing Contexts: METAL(B) and METAL(IB)

Third International Conference on Multistrategy Learning

Volume

Third International Conference on Multistrategy Learning

Contents

This paper concentrates on a class of learning tasks where the domain provides explicit clues as to the current context (e.g., attributes with characteristic values). A general two-level learning model is presented that effectively adjusts to changing contexts by trying to detect (via meter learning) contextual clues and using this information to focus the learning process. Context learning and detection occur during regular online learning, without separate training phases for context recognition.