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GECCO
2007
Springer
194views Optimization» more  GECCO 2007»
14 years 3 months ago
Hybrid coevolutionary algorithms vs. SVM algorithms
As a learning method support vector machine is regarded as one of the best classifiers with a strong mathematical foundation. On the other hand, evolutionary computational techniq...
Rui Li, Bir Bhanu, Krzysztof Krawiec
TNN
2010
205views Management» more  TNN 2010»
13 years 3 months ago
Behavior-constrained support vector machines for fMRI data analysis
Statistical learning methods are emerging as a valuable tool for decoding information from neural imaging data. The noisy signal and the limited number of training patterns that ar...
Danmei Chen, Sheng Li, Zoe Kourtzi, Si Wu
ACL
2007
13 years 10 months ago
Support Vector Machines for Query-focused Summarization trained and evaluated on Pyramid data
This paper presents the use of Support Vector Machines (SVM) to detect relevant information to be included in a queryfocused summary. Several SVMs are trained using information fr...
María Fuentes Fort, Enrique Alfonseca, Hora...
ICPR
2002
IEEE
14 years 10 months ago
Object Detection in Images: Run-Time Complexity and Parameter Selection of Support Vector Machines
In this paper we address two aspects related to the exploitation of Support Vector Machines (SVM) for classification in real application domains, such as the detection of objects ...
Nicola Ancona, Grazia Cicirelli, Ettore Stella, Ar...
ICPR
2006
IEEE
14 years 10 months ago
Feature selection for linear support vector machines
Feature selection is attracted much interest from researchers in many fields such as pattern recognition and data mining. In this paper, a novel algorithm for feature selection is...
Zhizheng Liang, Tuo Zhao