We propose a representation for musical chords that allows us to include domain knowledge in probabilistic models. We then introduce a graphical model for harmonization of melodies...
Mixtures of probabilistic principal component analyzers model high-dimensional nonlinear data by combining local linear models. Each mixture component is specifically designed to...
Research over the past several decades in learning logical and probabilistic models has greatly increased the range of phenomena that machine learning can address. Recent work has ...
Researchers often express probabilistic planning problems as Markov decision process models and then maximize the expected total reward. However, it is often rational to maximize ...
A new probabilistic image segmentation model based on hypothesis testing and Gibbs Random Fields is introduced. First, a probabilistic difference measure derived from a set of hyp...