Optimized realization of Bayesian networks in reduced normal form using latent variable model
نویسندگان
چکیده
Abstract Bayesian networks in their Factor Graph Reduced Normal Form are a powerful paradigm for implementing inference graphs. Unfortunately, the computational and memory costs of these may be considerable even relatively small networks, this is one main reasons why structures have often been underused practice. In work, through detailed algorithmic structural analysis, various solutions cost reduction proposed. Moreover, an online version classic batch learning algorithm also analysed, showing very similar results unsupervised context but with much better performance; which essential if multi-level to built. The proposed, together possible algorithm, included C++ library that quite efficient, especially compared direct use well-known sum-product Maximum Likelihood algorithms. obtained discussed particular reference Latent Variable Model structure.
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ژورنال
عنوان ژورنال: Soft Computing
سال: 2021
ISSN: ['1433-7479', '1432-7643']
DOI: https://doi.org/10.1007/s00500-021-05642-3