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» A Guided Monte Carlo Approach to Optimization Problems
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SEAL
2010
Springer
13 years 5 months ago
Generating Sequential Space-Filling Designs Using Genetic Algorithms and Monte Carlo Methods
In this paper, the authors compare a Monte Carlo method and an optimization-based approach using genetic algorithms for sequentially generating space-filling experimental designs....
Karel Crombecq, Tom Dhaene
BMCBI
2004
177views more  BMCBI 2004»
13 years 7 months ago
Gapped alignment of protein sequence motifs through Monte Carlo optimization of a hidden Markov model
Background: Certain protein families are highly conserved across distantly related organisms and belong to large and functionally diverse superfamilies. The patterns of conservati...
Andrew F. Neuwald, Jun S. Liu
ECCV
2006
Springer
14 years 9 months ago
Globally Optimal Active Contours, Sequential Monte Carlo and On-Line Learning for Vessel Segmentation
In this paper we propose a Particle Filter-based propagation approach for the segmentation of vascular structures in 3D volumes. Because of pathologies and inhomogeneities, many de...
Charles Florin, Nikos Paragios, James Williams
NIPS
2000
13 years 8 months ago
Feature Correspondence: A Markov Chain Monte Carlo Approach
When trying to recover 3D structure from a set of images, the most di cult problem is establishing the correspondence between the measurements. Most existing approaches assume tha...
Frank Dellaert, Steven M. Seitz, Sebastian Thrun, ...
ICCAD
2007
IEEE
96views Hardware» more  ICCAD 2007»
14 years 4 months ago
Monte-Carlo driven stochastic optimization framework for handling fabrication variability
Increasing effects of fabrication variability have inspired a growing interest in statistical techniques for design optimization. In this work, we propose a Monte-Carlo driven sto...
Vishal Khandelwal, Ankur Srivastava