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Robustná variačná inferencia×Bayesovská regresia×
OdborBayesovské metódyBayesovské metódy
RodinaBayesian methodsBayesian methods
Rok vzniku2008-2018
TvorcaFujisawa & Eguchi (2008); Futami, Sato & Sugiyama (2018)
TypRobust approximate Bayesian inferenceBayesian linear model
Pôvodný zdrojFutami, F., Sato, I. & Sugiyama, M. (2018). Variational inference based on robust divergences. Proceedings of the 21st International Conference on Artificial Intelligence and Statistics (AISTATS), PMLR 84:813-822. link ↗Gelman, A., Carlin, J. B., Stern, H. S., Dunson, D. B., Vehtari, A. & Rubin, D. B. (2013). Bayesian Data Analysis (3rd ed.). CRC Press. ISBN: 978-1439840955
Ďalšie názvyRVI, robust VI, outlier-robust variational Bayes, power-divergence variational inferencebayesian linear regression, probabilistic regression, bayesian regresyon
Príbuzné62
ZhrnutieRobust variational inference (RVI) extends standard variational inference by replacing the Kullback-Leibler divergence with a divergence measure that is less sensitive to outliers and model misspecification — such as the beta-divergence or a Renyi-type divergence. This yields posterior approximations that remain well-behaved even when a fraction of the data departs from the assumed model.Bayesian regression is a probabilistic version of linear regression that treats the model parameters as uncertain quantities. Instead of returning a single best-fit estimate, it combines prior knowledge with the observed data to produce a full posterior probability distribution for each parameter, from which credible intervals and predictions are read off.
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ScholarGatePorovnať metódy: Robust Variational Inference · Bayesian Regression. Získané 2026-06-17 z https://scholargate.app/sk/compare