@inproceedings{Poland:05mdlreg,
        title = {Strong Asymptotic Assertions for Discrete {MDL} in Regression and Classification},
        address = {Enschede},
        author = {J. Poland and M. Hutter},
        booktitle = {Annual Machine Learning Conference of Belgium and the Netherlands ({Benelearn-2005})},
        year = 2005,
        url = {http://arxiv.org/abs/math.ST/0502315},
        id = {2382166},
	priority = {2},
	biburl = {http://www.bibsonomy.org/bibtex/28319bdd4f41d45232efb7965421e9f9b/idsia},
	keywords = {regression, length, juergen, convergence, description, classification, learning, discrete, prediction, minimum, bayes, sequence marginalization, machine, mixture, classes, model,}
}

@article{Hutter:04mifs,
        title = {Distribution of Mutual Information from Complete and Incomplete Data},
        author = {Marcus Hutter and Marco Zaffalon},
        journal = {Computational Statistics \& Data Analysis},
        number = 3,
        pages = {633--657},
        publisher = {Elsevier Science},
        volume = 48,
        year = 2005,
        url = {http://www.hutter1.de/ai/mifs.htm},
        id = {2382178},
	priority = {2},
	biburl = {http://www.bibsonomy.org/bibtex/23e33239f0046b223f066a4fbe60edcd6/idsia},
	keywords = {cross, feature, bayesian, order, of, juergen, mutual, variance distribution, and, expectation, bayes, naive, dirichlet, second, statistics, information, selection, entropy, filters, classifier,}
}

@inproceedings{Zaffalon:02feature,
        title = {Robust Feature Selection by Mutual Information Distributions},
        author = {Marco Zaffalon and Marcus Hutter},
        booktitle = {Proc. 18th International Conf. on Uncertainty in Artificial Intelligence (UAI-2002)},
        pages = {577--584},
        publisher = {Morgan Kaufmann, San Francisco, CA},
        year = 2002,
        url = {http://arxiv.org/abs/cs.AI/0206006},
        id = {2382179},
	priority = {2},
	biburl = {http://www.bibsonomy.org/bibtex/2f65403f6346a5b6747be35f3f4f3ac2f/idsia},
	keywords = {bayesian, order, mutual, distribution, missing, and, expectation, naive, robust, information, selection, entropy, feature, data, cross, of, juergen, variance credible, bayes, dirichlet, filter, second, intervals, statistics, approach, classifier,}
}