Bayes universal coding algorithm for side information context tree models

The problem of universal codes with side information is investigated from Bayes criterion. We propose side information context tree models which are an extension of context tree models to sources with side information. Assuming a special class of the prior distributions for side information context tree models, we propose an efficient algorithm of Bayes code for the models. The asymptotic code length of the Bayes codes with side information is also investigated