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...
Recent research works on unsupervised word sense disambiguation report an increase in performance, which reduces their handicap from the respective supervised approaches for the sa...
George Tsatsaronis, Iraklis Varlamis, Kjetil N&osl...
We present a probabilistic graphical model for point set matching. By using a result about the redundancy of the pairwise distances in a point set, we represent the binary relation...
We address the problem of detection and tracking of moving objects in a video stream obtained from a moving airborne platform. The proposed method relies on a graph representation...
: We address the problems of structuring and annotation of layout-oriented documents. We model the annotation problems as the collective classification on graph-like structures wit...