This site uses cookies to deliver our services and to ensure you get the best experience. By continuing to use this site, you consent to our use of cookies and acknowledge that you have read and understand our Privacy Policy, Cookie Policy, and Terms
Compression has been advocated as one of the principles which pervades inductive inference and prediction - and, from there, it has also been recurrent in definitions and tests of...
We describe a mechanism for the interpretation of arguments, which can cope with noisy conditions in terms of wording, beliefs and argument structure. This is achieved through the...
We present here some applications of the Minimum Message Length (MML) principle to spatially correlated data. Discrete valued Markov Random Fields are used to model spatial correl...
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)....
Abstract. In Minimum Message Length (MML) clustering (unsupervised classification, mixture modelling) the aim is to infer a set of classes that best explains the observed data ite...