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Variational Bayesian Methods: Variational Bayesian Methods, Bayesian Inference, Machine Learning, Integral, Marginal Likelihood, Likelihood Function, Nuisance Parameter, Model Selection -

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2026-03-22
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Please note that the content of this book primarily consists of articles available from Wikipedia or other free sources online. Variational Bayesian methods, also called ensemble learning, are a family of techniques for approximating intractable integrals arising in Bayesian statistics and machine learning. They can be used to lower bound the marginal likelihood of several models with a view to performing m ... Visas aprašymas

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Please note that the content of this book primarily consists of articles available from Wikipedia or other free sources online. Variational Bayesian methods, also called ensemble learning, are a family of techniques for approximating intractable integrals arising in Bayesian statistics and machine learning. They can be used to lower bound the marginal likelihood of several models with a view to performing model selection, and often provide an analytical approximation to the parameter posterior probability which is useful for prediction. It is an alternative to Monte Carlo sampling methods for making use of a posterior distribution that is difficult to sample from directly.

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Leidėjas OmniScriptum
Išleidimo metai 2026
Viršelio tipas Minkšti viršeliai
EAN 9786130335021
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146,80 € 195,73 €