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» Messy Genetic Algorithms for Subset Feature Selection
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GECCO
2008
Springer
130views Optimization» more  GECCO 2008»
13 years 8 months ago
VoIP speech quality estimation in a mixed context with genetic programming
Voice over IP (VoIP) speech quality estimation is crucial to providing optimal Quality of Service (QoS). This paper seeks to provide improved speech quality estimation models with...
Adil Raja, R. Muhammad Atif Azad, Colin Flanagan, ...
CVPR
2007
IEEE
14 years 9 months ago
Detecting Pedestrians by Learning Shapelet Features
In this paper, we address the problem of detecting pedestrians in still images. We introduce an algorithm for learning shapelet features, a set of mid?level features. These featur...
Payam Sabzmeydani, Greg Mori
IWANN
2009
Springer
14 years 1 months ago
RCGA-S/RCGA-SP Methods to Minimize the Delta Test for Regression Tasks
Frequently, the number of input variables (features) involved in a problem becomes too large to be easily handled by conventional machine-learning models. This paper introduces a c...
Fernando Mateo, Dusan Sovilj, Rafael Gadea Giron&e...
TEC
2002
133views more  TEC 2002»
13 years 7 months ago
Learning and optimization using the clonal selection principle
The clonal selection principle is used to explain the basic features of an adaptive immune response to an antigenic stimulus. It establishes the idea that only those cells that rec...
Leandro Nunes de Castro, Fernando J. Von Zuben
MCS
2007
Springer
14 years 1 months ago
Selecting Diversifying Heuristics for Cluster Ensembles
Abstract. Cluster ensembles are deemed to be better than single clustering algorithms for discovering complex or noisy structures in data. Various heuristics for constructing such ...
Stefan Todorov Hadjitodorov, Ludmila I. Kuncheva