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- W2010058975 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." @default.
- W2010058975 created "2016-06-24" @default.
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- W2010058975 date "2004-01-01" @default.
- W2010058975 modified "2023-09-25" @default.
- W2010058975 title "Sequential information bottleneck for finite data" @default.
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- W2010058975 doi "https://doi.org/10.1145/1015330.1015375" @default.
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