85 search results - page 14 / 17 » Genetic Programming and Deductive-Inductive Learning: A Mult... |
GECCO
2007
Springer
14 years 1 months ago
2007
Springer
In this paper we propose a genetic programming approach to learning stochastic models with unsymmetrical noise distributions. Most learning algorithms try to learn from noisy data...
EC
2008
13 years 7 months ago
2008
The development of successful metaheuristic algorithms such as local search for a difficult problems such as satisfiability testing (SAT) is a challenging task. We investigate an ...
AAAI
2007
13 years 9 months ago
2007
Analysis of postgenomic biological data (such as microarray and SNP data) is a subtle art and science, and the statistical methods most commonly utilized sometimes prove inadequat...
KES
2006
Springer
13 years 7 months ago
2006
Springer
Abstract. The aim of this work is to forecast future events in financial data sets, in particular, we focus our attention on situations where positive instances are rare, which fal...
ISCA
1997
IEEE
13 years 11 months ago
1997
IEEE
As processor architectures have increased their reliance on speculative execution to improve performance, the importance of accurate prediction of what to execute speculatively ha...