A Tighter Bound for Graphical Models

26 citations recorded by the source corpus.

How researchers see this paper

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Variational Inference: A Review for Statisticians (2016, background): “Other work has developed divergences based on lower bounds that are tighter than the ELBO (Barber and de van Laar 1999; Leisink and Kappen 2001).”
Bayesian reasoning and machine learning (2012, unknown): “7) The significance is that this double integration (or summation in the case of discrete variables) is a general procedure for generating a new bound from an existing bound [172].”
Graphical Models, Exponential Families, and Variational Inference (2008, background): “Leisinck and Kappen [153] proposed a class of higher-order expansions that generate tighter lower bounds.”
A new class of upper bounds on the log partition function (2002, methodology): “By using higher order expansions, Leisink and Kappen [25] derived lower bounds that are tighter than naive mean field.”
Variational Bayesian Inference with Stochastic Search (2012, methodology): “Therefore, much attention has been paid to developing tight bounds of commonly occurring functions (e.g., Jaakkola & Jordan (2000), Marlin et al. (2011), Leisink & Kappen (2001)).”