A new, general approach is described for approximate inference in first-order probabilistic languages, using Markov chain Monte Carlo (MCMC) techniques in the space of concrete po...
This paper introduces and describes an innovative modelling approach which utilises models that are synthesised through approximate calculations of user actions and extensive repr...
We initiate the study of the computational complexity of the covering radius problem for point lattices, and approximation versions of the problem for both lattices and linear cod...
Data stream analysis frequently relies on identifying correlations and posing conditional queries on the data after it has been seen. Correlated aggregates form an important examp...
The 2-class transduction problem, as formulated by Vapnik [1], involves finding a separating hyperplane for a labelled data set that is also maximally distant from a given set of...