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GECCO
2010
Springer
218views Optimization» more  GECCO 2010»
13 years 10 months ago
Cartesian genetic programming
This paper presents a new form of Genetic Programming called Cartesian Genetic Programming in which a program is represented as an indexed graph. The graph is encoded in the form o...
Julian Francis Miller, Simon L. Harding
SODA
2010
ACM
143views Algorithms» more  SODA 2010»
13 years 4 months ago
Thin Partitions: Isoperimetric Inequalities and a Sampling Algorithm for Star Shaped Bodies
Star-shaped bodies are an important nonconvex generalization of convex bodies (e.g., linear programming with violations). Here we present an efficient algorithm for sampling a giv...
Karthekeyan Chandrasekaran, Daniel Dadush, Santosh...
GECCO
2006
Springer
186views Optimization» more  GECCO 2006»
13 years 9 months ago
Characterizing large text corpora using a maximum variation sampling genetic algorithm
An enormous amount of information available via the Internet exists. Much of this data is in the form of text-based documents. These documents cover a variety of topics that are v...
Robert M. Patton, Thomas E. Potok
GECCO
2005
Springer
159views Optimization» more  GECCO 2005»
13 years 11 months ago
Resource-limited genetic programming: the dynamic approach
Resource-Limited Genetic Programming is a bloat control technique that imposes a single limit on the total amount of resources available to the entire population, where resources ...
Sara Silva, Ernesto Costa
ICML
2003
IEEE
13 years 11 months ago
Evolutionary MCMC Sampling and Optimization in Discrete Spaces
The links between genetic algorithms and population-based Markov Chain Monte Carlo (MCMC) methods are explored. Genetic algorithms (GAs) are well-known for their capability to opt...
Malcolm J. A. Strens