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GECCO
2004
Springer
144views Optimization» more  GECCO 2004»
15 years 8 months ago
Feature Subset Selection, Class Separability, and Genetic Algorithms
Abstract. The performance of classification algorithms in machine learning is affected by the features used to describe the labeled examples presented to the inducers. Therefore,...
Erick Cantú-Paz
GECCO
2005
Springer
139views Optimization» more  GECCO 2005»
15 years 8 months ago
A genetic algorithm for unmanned aerial vehicle routing
Genetic Algorithms (GAs) can efficiently produce high quality results for hard combinatorial real world problems such as the Vehicle Routing Problem (VRP). Genetic Vehicle Represe...
Matthew A. Russell, Gary B. Lamont
IJCAI
2007
15 years 4 months ago
Fast Image Alignment Using Anytime Algorithms
Image alignment refers to finding the best transformation from a fixed reference image to a new image of a scene. This process is often guided by similarity measures between ima...
Rupert Brooks, Tal Arbel, Doina Precup
KDD
2002
ACM
147views Data Mining» more  KDD 2002»
16 years 3 months ago
Sequential cost-sensitive decision making with reinforcement learning
Recently, there has been increasing interest in the issues of cost-sensitive learning and decision making in a variety of applications of data mining. A number of approaches have ...
Edwin P. D. Pednault, Naoki Abe, Bianca Zadrozny
KDD
2006
ACM
213views Data Mining» more  KDD 2006»
16 years 3 months ago
Learning sparse metrics via linear programming
Calculation of object similarity, for example through a distance function, is a common part of data mining and machine learning algorithms. This calculation is crucial for efficie...
Glenn Fung, Rómer Rosales