Adaptor grammars are a framework for expressing and performing inference over a variety of non-parametric linguistic models. These models currently provide state-of-the-art perfor...
A dependent hierarchical beta process (dHBP) is developed as a prior for data that may be represented in terms of a sparse set of latent features (dictionary elements), with covar...
The minimum message length (MML) principle for inductive inference has been successfully applied to image segmentation where the images are modelled by Markov random fields (MRF)....
This paper reviews algorithms for local computation with imprecise probabilities. These algorithms try to solve problems of inference calculation of conditional or unconditional p...
Abstract. Synchronous languages are well suited for the design of dependable real-time systems: they enable a very high-level specification and an extremely modular implementation ...