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GECCO
2009
Springer
134views Optimization» more  GECCO 2009»
14 years 1 months ago
Estimating the distribution and propagation of genetic programming building blocks through tree compression
Shin et al [19] and McKay et al [15] previously applied tree compression and semantics-based simplification to study the distribution of building blocks in evolving Genetic Progr...
Robert I. McKay, Xuan Hoai Nguyen, James R. Cheney...
GECCO
2008
Springer
192views Optimization» more  GECCO 2008»
13 years 10 months ago
Non-linear factor model for asset selection using multi objective genetic programming
Investors vary with respect to their expected return and aversion to associated risk, and hence also vary in their performance expectations of the stock market portfolios they hol...
Ghada Hassan
EUROGP
2009
Springer
125views Optimization» more  EUROGP 2009»
14 years 3 months ago
The Role of Population Size in Rate of Evolution in Genetic Programming
Abstract. Population size is a critical parameter that affects the performance of an Evolutionary Computation model. A variable population size scheme is considered potentially be...
Ting Hu, Wolfgang Banzhaf
VTC
2006
IEEE
152views Communications» more  VTC 2006»
14 years 2 months ago
Cross-Layer Resource Allocation via Geometric Programming in Fading Broadcast Channels
Abstract— In a fading broadcast channel (BC), Queue Proportional Scheduling (QPS) is presented via geometric programming (GP). Given the current queue state, QPS allocates a data...
Kibeom Seong, Ravi Narasimhan, John M. Cioffi
EVOW
2003
Springer
14 years 2 months ago
Comparison of AdaBoost and Genetic Programming for Combining Neural Networks for Drug Discovery
Genetic programming (GP) based data fusion and AdaBoost can both improve in vitro prediction of Cytochrome P450 activity by combining artificial neural networks (ANN). Pharmaceuti...
William B. Langdon, S. J. Barrett, Bernard F. Buxt...