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» Genetic Algorithms and Explicit Search Statistics
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CVPR
2001
IEEE
14 years 9 months ago
Automatic Partitioning of High Dimensional Search Spaces Associated with Articulated Body Motion Capture
Particle filters have proven to be an effective tool for visual tracking in non-gaussian, cluttered environments. Conventional particle filters however do not scale to the problem...
Jonathan Deutscher, Andrew J. Davison, Ian D. Reid
GECCO
2007
Springer
163views Optimization» more  GECCO 2007»
14 years 1 months ago
Exploring medical data using visual spaces with genetic programming and implicit functional mappings
Two medical data sets (Breast cancer and Colon cancer) are investigated within a visual data mining paradigm through the unsupervised construction of virtual reality spaces using ...
Julio J. Valdés, Robert Orchard, Alan J. Ba...
GECCO
2005
Springer
100views Optimization» more  GECCO 2005»
14 years 1 months ago
Evolutionary tree genetic programming
We introduce a clustering-based method of subpopulation management in genetic programming (GP) called Evolutionary Tree Genetic Programming (ETGP). The biological motivation behin...
Ján Antolík, William H. Hsu
EC
2008
103views ECommerce» more  EC 2008»
13 years 7 months ago
A Graphical Model for Evolutionary Optimization
We present a statistical model of empirical optimization that admits the creation of algorithms with explicit and intuitively defined desiderata. Because No Free Lunch theorems di...
Christopher K. Monson, Kevin D. Seppi
GECCO
2007
Springer
187views Optimization» more  GECCO 2007»
14 years 1 months ago
Defining implicit objective functions for design problems
In many design tasks it is difficult to explicitly define an objective function. This paper uses machine learning to derive an objective in a feature space based on selected examp...
Sean Hanna