Abstract. The Bayesian approach to machine learning amounts to inferring posterior distributions of random variables from a probabilistic model of how the variables are related (th...
The max-sum classifier predicts n-tuple of labels from n-tuple of observable variables by maximizing a sum of quality functions defined over neighbouring pairs of labels and obser...
Abstract. Approaches to visual navigation, e.g. used in robotics, require computationally efficient, numerically stable, and robust methods for the estimation of ego-motion. One of...
Abstract. A resource selection probability function is a function that gives the probability that a resource unit (e.g., a plot of land) that is described by a set of habitat varia...
This paper describes how a visual system can automatically define features of interest from the observation of a large enough number of natural images. The principle complements t...