711 search results - page 25 / 143 » An Empirical Comparison of Selection Methods in Evolutionary... |
PPSN
2004
Springer
14 years 1 months ago
2004
Springer
Multi-objective optimization methods are essential to resolve real-world problems as most involve several types of objects. Several multi-objective genetic algorithms have been pro...
EMNLP
2008
13 years 9 months ago
2008
Active learning is well-suited to many problems in natural language processing, where unlabeled data may be abundant but annotation is slow and expensive. This paper aims to shed ...
GECCO
2006
Springer
13 years 11 months ago
2006
Springer
In this paper, we address the problem of finding gene regulatory networks from experimental DNA microarray data. We focus on the evaluation of the performance of different evoluti...
BMCBI
2010
13 years 7 months ago
2010
Background: Microarray data discretization is a basic preprocess for many algorithms of gene regulatory network inference. Some common discretization methods in informatics are us...
EPIA
2007
Springer
14 years 1 months ago
2007
Springer
The goal of an Evolutionary Algorithm(EA) is to find the optimal solution to a given problem by evolving a set of initial potential solutions. When the problem is multi-modal, an ...