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» Are Multiple Runs of Genetic Algorithms Better than One
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GECCO
2003
Springer
103views Optimization» more  GECCO 2003»
13 years 10 months ago
Are Multiple Runs of Genetic Algorithms Better than One?
Abstract. There are conflicting reports over whether multiple independent runs of genetic algorithms (GAs) with small populations can reach solutions of higher quality or can fin...
Erick Cantú-Paz, David E. Goldberg
NAACL
2003
13 years 6 months ago
In Question Answering, Two Heads Are Better Than One
Motivated by the success of ensemble methods in machine learning and other areas of natural language processing, we developed a multistrategy and multi-source approach to question...
Jennifer Chu-Carroll, Krzysztof Czuba, John M. Pra...
SIGIR
2010
ACM
13 years 9 months ago
Many are better than one: improving multi-document summarization via weighted consensus
Given a collection of documents, various multi-document summarization methods have been proposed to generate a short summary. However, few studies have been reported on aggregatin...
Dingding Wang, Tao Li
ICMLA
2008
13 years 6 months ago
Decision Tree Ensemble: Small Heterogeneous Is Better Than Large Homogeneous
Using decision trees that split on randomly selected attributes is one way to increase the diversity within an ensemble of decision trees. Another approach increases diversity by ...
Michael Gashler, Christophe G. Giraud-Carrier, Ton...
GECCO
2004
Springer
137views Optimization» more  GECCO 2004»
13 years 10 months ago
Evolving Better Multiple Sequence Alignments
Aligning multiple DNA or protein sequences is a fundamental step in the analyses of phylogeny, homology and molecular structure. Heuristic algorithms are applied because optimal mu...
Luke Sheneman, James A. Foster