We apply a type of generative modelling to the problem of blind source separation in which prior knowledge about the latent source signals, such as time-varying auto-correlation a...
We present worst case bounds for the learning rate of a known prediction method that is based on hierarchical applications of binary context tree weighting (CTW) predictors. A heu...
This paper proposes a general probabilistic framework for shape-based modeling and classification of waveform data. A segmental hidden Markov model (HMM) is used to characterize w...
Ensemble methods that train multiple learners and then combine their predictions have been shown to be very effective in supervised learning. This paper explores ensemble methods ...
We describe an algorithm for context-based segmentation of visual data. New frames in an image sequence (video) are segmented based on the prior segmentation of earlier frames in ...