Existing content-based publish/subscribe systems are designed assuming that all matching publications are equally relevant to a subscription. As we cannot know in advance the dist...
Kresimir Pripuzic, Ivana Podnar Zarko, Karl Aberer
Markov Random Field, or MRF, models are a powerful tool for modeling images. While much progress has been made in algorithms for inference in MRFs, learning the parameters of an M...
We propose a new model for the probabilistic estimation of continuous state variables from a sequence of observations, such as tracking the position of an object in video. This ma...
Problems with legal quality will not only increase effort and costs of the law enforcement organisations, but also undermines the regulating power of the legislator. Unintended us...
We introduce a probabilistic formalism subsuming Markov random fields of bounded tree width and probabilistic context free grammars. Our models are based on a representation of Bo...
David A. McAllester, Michael Collins, Fernando Per...