29 search results - page 4 / 6 » Counting Solution Clusters in Graph Coloring Problems Using ... |
UAI
2008
13 years 7 months ago
2008
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...
CVPR
2000
IEEE
13 years 10 months ago
2000
IEEE
We use cluster analysis as a unifying principle for problems from low, middle and high level vision. The clustering problem is viewed as graph partitioning, where nodes represent ...
CVPR
2004
IEEE
13 years 9 months ago
2004
IEEE
Graphical models are powerful tools for processing images. However, the large dimensionality of even local image data poses a difficulty: representing the range of possible graphi...
CVPR
2010
IEEE
14 years 2 months ago
2010
IEEE
Maximum a posteriori (MAP) inference in Markov Random Fields (MRFs) is an NP-hard problem, and thus research has focussed on either finding efficiently solvable subclasses (e.g. t...
CVPR
2010
IEEE
14 years 1 months ago
2010
IEEE
Conditional Random Field models have proved effective for several low-level computer vision problems. Inference in these models involves solving a combinatorial optimization probl...