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ibp

于 2014-11-07 发布 文件大小:8172KB
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  Included in this distribution is matlab code to generate posterior samples for linear Gaussian and binary matrix factorization (noisy-or) Indian Buffet Process models. Three different posterior sampling algorithms are provided: Gibbs, reversible jump Markov chain Monte Carlo (RJMCMC), and sequential importance sampling (SIS). Only the Gibbs and SIS samplers are provided for the linear Gaussian IBP models.

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