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UAI
2008
15 years 1 months ago
Bounds on the Bethe Free Energy for Gaussian Networks
We address the problem of computing approximate marginals in Gaussian probabilistic models by using mean field and fractional Bethe approximations. As an extension of Welling and ...
Botond Cseke, Tom Heskes
CVPR
2009
IEEE
15 years 10 months ago
Markov Chain Monte Carlo Combined with Deterministic Methods for Markov Random Field Optimization
Many vision problems have been formulated as en- ergy minimization problems and there have been signif- icant advances in energy minimization algorithms. The most widely-used energ...
Wonsik Kim (Seoul National University), Kyoung Mu ...
ECCV
2008
Springer
15 years 10 months ago
Window Annealing over Square Lattice Markov Random Field
Monte Carlo methods and their subsequent simulated annealing are able to minimize general energy functions. However, the slow convergence of simulated annealing compared with more ...
Ho Yub Jung, Kyoung Mu Lee, Sang Uk Lee
CISS
2010
IEEE
14 years 3 months ago
Unconstrained minimization of quadratic functions via min-sum
—Gaussian belief propagation is an iterative algorithm for computing the mean of a multivariate Gaussian distribution. Equivalently, the min-sum algorithm can be used to compute ...
Nicholas Ruozzi, Sekhar Tatikonda
SIAMIS
2010
141views more  SIAMIS 2010»
14 years 6 months ago
Optimization by Stochastic Continuation
Simulated annealing (SA) and deterministic continuation are well-known generic approaches to global optimization. Deterministic continuation is computationally attractive but produ...
Marc C. Robini, Isabelle E. Magnin