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» New Algorithms for Learning in Presence of Errors
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GECCO
2005
Springer
119views Optimization» more  GECCO 2005»
14 years 2 months ago
Learning, anticipation and time-deception in evolutionary online dynamic optimization
In this paper we focus on an important source of problem– difficulty in (online) dynamic optimization problems that has so far received significantly less attention than the tr...
Peter A. N. Bosman
ICARCV
2006
IEEE
180views Robotics» more  ICARCV 2006»
14 years 2 months ago
Simultaneous Localization and Mapping with Stereo Vision
— In the simultaneous localization and mapping (SLAM) problem, a mobile robot must build a map of its environment while simultaneously determining its location within that map. W...
Matthew N. Dailey, Manukid Parnichkun
WSC
2007
13 years 11 months ago
Transformations for accelerating MCMC simulations with broken ergodicity
A new approach for overcoming broken ergodicity in Markov Chain Monte Carlo (MCMC) simulations of complex systems is described. The problem of broken ergodicity is often present i...
Mark Fleischer
BMCBI
2005
126views more  BMCBI 2005»
13 years 8 months ago
GANN: Genetic algorithm neural networks for the detection of conserved combinations of features in DNA
Background: The multitude of motif detection algorithms developed to date have largely focused on the detection of patterns in primary sequence. Since sequence-dependent DNA struc...
Robert G. Beiko, Robert L. Charlebois
ECCV
1998
Springer
14 years 10 months ago
Active Appearance Models
?We describe a new method of matching statistical models of appearance to images. A set of model parameters control modes of shape and gray-level variation learned from a training ...
Timothy F. Cootes, Gareth J. Edwards, Christopher ...