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» Learning Generative Models with the Up-Propagation Algorithm
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GECCO
2008
Springer
177views Optimization» more  GECCO 2008»
13 years 8 months ago
Reduced computation for evolutionary optimization in noisy environment
Evolutionary Algorithms’ (EAs’) application to real world optimization problems often involves expensive fitness function evaluation. Naturally this has a crippling effect on ...
Maumita Bhattacharya
CGF
2008
192views more  CGF 2008»
13 years 7 months ago
Non-Rigid Registration Under Isometric Deformations
We present a robust and efficient algorithm for the pairwise non-rigid registration of partially overlapping 3D surfaces. Our approach treats non-rigid registration as an optimiza...
Qi-Xing Huang, Bart Adams, Martin Wicke, Leonidas ...
ICDM
2003
IEEE
158views Data Mining» more  ICDM 2003»
14 years 29 days ago
Combining Multiple Weak Clusterings
A data set can be clustered in many ways depending on the clustering algorithm employed, parameter settings used and other factors. Can multiple clusterings be combined so that th...
Alexander P. Topchy, Anil K. Jain, William F. Punc...
ICCV
2007
IEEE
14 years 9 months ago
3D Variational Brain Tumor Segmentation using a High Dimensional Feature Set
Tumor segmentation from MRI data is an important but time consuming task performed manually by medical experts. Automating this process is challenging due to the high diversity in...
Albert Murtha, Dana Cobzas, Mark Schmidt, Martin J...
TEC
2008
104views more  TEC 2008»
13 years 7 months ago
Coevolution of Fitness Predictors
Abstract--We present an algorithm that coevolves fitness predictors, optimized for the solution population, which reduce fitness evaluation cost and frequency, while maintaining ev...
Michael D. Schmidt, Hod Lipson