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JAIR
2011
114views more  JAIR 2011»
14 years 9 months ago
Properties of Bethe Free Energies and Message Passing in Gaussian Models
We address the problem of computing approximate marginals in Gaussian probabilistic models by using mean field and fractional Bethe approximations. We define the Gaussian fracti...
Botond Cseke, Tom Heskes
SCALESPACE
2007
Springer
16 years 15 days ago
On the Statistical Interpretation of the Piecewise Smooth Mumford-Shah Functional
In region-based image segmentation, two models dominate the field: the Mumford-Shah functional and statistical approaches based on Bayesian inference. Whereas the latter allow for...
Thomas Brox, Daniel Cremers
HIPC
2007
Springer
15 years 10 months ago
Accomplishing Approximate FCFS Fairness Without Queues
First Come First Served (FCFS) is a policy that is accepted for implementing fairness in a number of application domains such as scheduling in Operating Systems, scheduling web req...
K. Subramani, Kamesh Madduri
SIAMSC
2011
219views more  SIAMSC 2011»
15 years 1 months ago
Fast Algorithms for Bayesian Uncertainty Quantification in Large-Scale Linear Inverse Problems Based on Low-Rank Partial Hessian
We consider the problem of estimating the uncertainty in large-scale linear statistical inverse problems with high-dimensional parameter spaces within the framework of Bayesian inf...
H. P. Flath, Lucas C. Wilcox, Volkan Akcelik, Judi...
ICML
2010
IEEE
15 years 7 months ago
Learning Efficiently with Approximate Inference via Dual Losses
Many structured prediction tasks involve complex models where inference is computationally intractable, but where it can be well approximated using a linear programming relaxation...
Ofer Meshi, David Sontag, Tommi Jaakkola, Amir Glo...