منابع مشابه
Cavity approximation for graphical models.
We reformulate the cavity approximation (CA), a class of algorithms recently introduced for improving the Bethe approximation estimates of marginals in graphical models. In our formulation, which allows for the treatment of multivalued variables, a further generalization to factor graphs with arbitrary order of interaction factors is explicitly carried out, and a message passing algorithm that ...
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– We investigate numerically the Cavity Approximation (CA), a class of algorithms recently introduced for improving the Bethe approximation estimates of marginals in graphical models. In the case of models defined on random graphs of size N we confirm the original expectation that CA[k], the approximation of order k, yields estimates with an error of order O(1/N) with polynomial computational c...
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The Collective Graphical Model (CGM) models a population of independent and identically distributed individuals when only collective statistics (i.e., counts of individuals) are observed. Exact inference in CGMs is intractable, and previous work has explored Markov Chain Monte Carlo (MCMC) and MAP approximations for learning and inference. This paper studies Gaussian approximations to the CGM. ...
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Machine learning on resource constrained ubiquitous devices suffers from high energy consumption and slow execution time. In this paper, it is investigated how to modify machine learning algorithms in order to reduce the number of consumed clock cycles—not by reducing the asymptotic complexity, but by assuming a weaker execution platform. In particular, an integer approximation to the class of ...
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We describe a new algorithmic framework for inference in probabilistic models, and apply it to inference for latent Dirichlet allocation (LDA). Our framework adopts the methodology of variational inference, but unlike existing variational methods such as mean field and expectation propagation it is not restricted to tractable classes of approximating distributions. Our approach can also be view...
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ژورنال
عنوان ژورنال: Physical Review E
سال: 2007
ISSN: 1539-3755,1550-2376
DOI: 10.1103/physreve.76.011102