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| Paper: | IMDSP-L2.3 |
| Session: | Image and Multidimensional Signal Processing: Theory |
| Time: | Wednesday, May 19, 16:10 - 16:30 |
| Presentation: |
Lecture |
| Topic: |
Image and Multidimensional Signal Processing: Image Formation and Computed Imaging |
| Title: |
HIERARCHICAL ANNEALING FOR SCIENTIFIC MODELS |
| Authors: |
Simon Alexander; University of Waterloo | | |
| | Edward Vrscay; University of Waterloo | | |
| | Paul Fieguth; University of Waterloo | | |
| Abstract: |
The computational complexity of simulated annealing makes it an impractical tool in many applications, particularly for complex, non-local models on very large 2D and 3D domains as desired in many scientific contexts. In particular, it is very difficult to produce large scale structure from a fine, pixellated lattice. Thus a hierarchical approach is intuitively attractive. However, existing approaches are few and limited. Motivated by a current problem in porous media, we develop a hierarchical approach to complex model sampling. In experiments, this approach results in 1--2 orders of magnitude computational gain, and significant gains in convergence as well. |
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