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We study the problem of quantization of discrete probability distributions, arising in universal coding, as well as other applications. We show, that in many situations this problem can be reduced to the covering problem for the unit simplex, yielding precise characterization in the high-rate regime. Our main contribution is a simple and asymptotically optimal algorithm for solving this problem. Performance...
We study the problem of coding of unordered sets of words, appearing in natural language processing, retrieval, machine learning, computer vision, and other fields. We note that this problem is different from the problem of coding of a particular sequence of same words, and show that up to log(m!) bits (where m is the number of words in the set) can be saved by specialized codes for sets. We propose...
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