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» Lagrangian Relaxation for MAP Estimation in Graphical Models
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ICML
2006
IEEE
14 years 6 months ago
Efficient MAP approximation for dense energy functions
We present an efficient method for maximizing energy functions with first and second order potentials, suitable for MAP labeling estimation problems that arise in undirected graph...
Marius Leordeanu, Martial Hebert
MICCAI
2009
Springer
14 years 8 days ago
Improved Maximum a Posteriori Cortical Segmentation by Iterative Relaxation of Priors
Abstract. Thickness measurements of the cerebral cortex can aid diagnosis and provide valuable information about the temporal evolution of several diseases such as Alzheimer’s, H...
Manuel Jorge Cardoso, Matthew J. Clarkson, Gerard ...
UAI
2008
13 years 6 months ago
Tightening LP Relaxations for MAP using Message Passing
Linear Programming (LP) relaxations have become powerful tools for finding the most probable (MAP) configuration in graphical models. These relaxations can be solved efficiently u...
David Sontag, Talya Meltzer, Amir Globerson, Tommi...
JMLR
2006
125views more  JMLR 2006»
13 years 5 months ago
Linear Programming Relaxations and Belief Propagation - An Empirical Study
The problem of finding the most probable (MAP) configuration in graphical models comes up in a wide range of applications. In a general graphical model this problem is NP hard, bu...
Chen Yanover, Talya Meltzer, Yair Weiss
VISUALIZATION
2005
IEEE
13 years 11 months ago
Surface Reconstruction Via Contour Metamorphosis: An Eulerian Approach With Lagrangian Particle Tracking
We present a robust method for 3D reconstruction of closed surfaces from sparsely sampled parallel contours. A solution to this problem is especially important for medical segment...
Ola Nilsson, David E. Breen, Ken Museth