A geometric view of conjugate priors

DOI10.1007/s10994-010-5203-xzbMath1470.68067OpenAlexW2085834335MaRDI QIDQ1959611

Arvind Agarwal, Hal Daumé

Publication date: 7 October 2010

Published in: Machine Learning (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/s10994-010-5203-x

zbMATH Keywords

exponential familiesconjugate priorBregman divergencegenerative models

Mathematics Subject Classification ID

Bayesian inference (62F15) Learning and adaptive systems in artificial intelligence (68T05) Information geometry (statistical aspects) (62B11)

Related Items (4)

Bayesian duality and risk analysis on the statistical manifold of exponential family with censored data ⋮ Information geometry on the curved \(q\)-exponential family with application to survival data analysis ⋮ Power transformations of relative count data as a shrinkage problem ⋮ On the geometry of Bayesian inference

Cites Work

• Unnamed Item
• Graphical Models, Exponential Families, and Variational Inference
• Divergence Function, Duality, and Convex Analysis
• Information geometry and prior selection

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