Adaptive Online Prediction Using Weighted Windows

We propose online prediction algorithms for data streams whose characteristics might change over time. Our algorithms are applications of online learning with experts. In particular, our algorithms combine base predictors over sliding windows with different length as experts. As a result, our algorithms are guaranteed to be competitive with the base predictor with the best fixed-length sliding window in hindsight.Special Section PAPER (Special Section on Information-Based Induction Sciences and Machine Learning

Adaptive Online Prediction Using Weighted Windows

Special Section PAPER (Special Section on Information-Based Induction Sciences and Machine Learning)We propose online prediction algorithms for data streams whose characteristics might change over time. Our algorithms are applications of online learning with experts. In particular, our algorithms combine base predictors over sliding windows with different length as experts. As a result, our algorithms are guaranteed to be competitive with the base predictor with the best fixed-length sliding window in hindsight