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Linear-Time Gibbs Sampling in Piecewise Graphical Models

Afshar, Hadi Mohasel; Sanner, Scott; Abbasnejad, Ehsan


Many real-world Bayesian inference problems such as preference learning or trader valuation modeling in financial markets naturally use piecewise likelihoods. Unfortunately, exact closed-form inference in the underlying Bayesian graphical models is intractable in the general case and existing approximation techniques provide few guarantees on both approximation quality and efficiency. While (Markov Chain) Monte Carlo methods provide an attractive asymptotically unbiased approximation approach,...[Show more]

CollectionsANU Research Publications
Date published: 2015
Type: Conference paper
Source: HVAC-Aware Occupancy Scheduling


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