This paper deals with the problem of inference under uncertain information. This is a generalization of a paper of Cardona et al. (1991a) where rules were not allowed to contain n...
Presence-absence (0-1) observations are special in that often the absence of evidence is not evidence of absence. Here we develop an independent factor model, which has the unique...
We extend the Bayesian skill rating system TrueSkill to infer entire time series of skills of players by smoothing through time instead of filtering. The skill of each participat...
Pierre Dangauthier, Ralf Herbrich, Tom Minka, Thor...
Noisy probabilistic relational rules are a promising world model representation for several reasons. They are compact and generalize over world instantiations. They are usually in...
Classification of real-world data poses a number of challenging problems. Mismatch between classifier models and true data distributions on one hand and the use of approximate inf...