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» Generalized crowding for genetic algorithms
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SAC
2006
ACM
14 years 9 months ago
Challenges in the compilation of a domain specific language for dynamic programming
Many combinatorial optimization problems in biosequence analysis are solved via dynamic programming. To increase programming productivity and program reliability, a domain specifi...
Robert Giegerich, Peter Steffen
KI
2010
Springer
14 years 8 months ago
An Extensible Modular Recognition Concept That Makes Activity Recognition Practical
Abstract. In mobile and ubiquitous computing, there is a strong need for supporting different users with different interests, needs, and demands. Activity recognition systems for c...
Martin Berchtold, Matthias Budde, Hedda Rahel Schm...
GECCO
2011
Springer
236views Optimization» more  GECCO 2011»
14 years 1 months ago
Online, GA based mixture of experts: a probabilistic model of ucs
In recent years there have been efforts to develop a probabilistic framework to explain the workings of a Learning Classifier System. This direction of research has met with lim...
Narayanan Unny Edakunni, Gavin Brown, Tim Kovacs
IHI
2012
370views Healthcare» more  IHI 2012»
13 years 5 months ago
FUSE: a system for data-driven multi-level functional summarization of protein interaction networks
Despite recent progress in high-throughput experimental studies, systems level visualization and analysis of large protein interaction networks (ppi) remains a challenging task, g...
Boon-Siew Seah, Sourav S. Bhowmick, Charles Forbes...
GECCO
2007
Springer
166views Optimization» more  GECCO 2007»
15 years 1 months ago
Crossover: the divine afflatus in search
The traditional GA theory is pillared on the Building Block Hypothesis (BBH) which states that Genetic Algorithms (GAs) work by discovering, emphasizing and recombining low order ...
David Iclanzan