@inproceedings{
    Peltonen04icml,
    editor = "Greiner, Russ and Schuurmans, Dale",
    author = "Peltonen, Jaakko and Sinkkonen, Janne and Kaski, Samuel",
    publisher = "Omnipress",
    title = "Sequential Information Bottleneck for Finite Data",
    url = "http://www.cis.hut.fi/projects/mi/papers/icml04.pdf",
    booktitle = "Proceedings of ICML 2004, the Twenty-First International Conference on Machine Learning",
    year = "2004",
    abstract = "The sequential information bottleneck (sIB) algorithm clusters co-occurrence data such as text documents vs. words. We introduce a variant that models sparse co-occurrence data by a generative process. This turns the objective function of sIB, mutual information, into a Bayes factor, while keeping it intact asymptotically, for non-sparse data. Experimental performance of the new algorithm is comparable to the original sIB for large data sets, and better for smaller, sparse sets.",
    flags = "AIRC copy",
    address = "Madison, WI",
    impactfactor = "D3",
    pages = "647-654"
}