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» Information theoretic combination of pattern classifiers
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KDD
2009
ACM
150views Data Mining» more  KDD 2009»
14 years 8 months ago
Information theoretic regularization for semi-supervised boosting
We present novel semi-supervised boosting algorithms that incrementally build linear combinations of weak classifiers through generic functional gradient descent using both labele...
Lei Zheng, Shaojun Wang, Yan Liu, Chi-Hoon Lee
LREC
2010
237views Education» more  LREC 2010»
13 years 9 months ago
Entity Mention Detection using a Combination of Redundancy-Driven Classifiers
We present an experimental framework for Entity Mention Detection in which two different classifiers are combined to exploit Data Redundancy attained through the annotation of a l...
Silvana Marianela Bernaola Biggio, Manuela Speranz...
GECCO
2009
Springer
194views Optimization» more  GECCO 2009»
14 years 2 months ago
Combining evolution strategy and gradient descent method for discriminative learning of bayesian classifiers
The optimization method is one of key issues in discriminative learning of pattern classifiers. This paper proposes a hybrid approach of the Covariance Matrix Adaptation Evolution...
Xuefeng Chen, Xiabi Liu, Yunde Jia
JVCIR
2006
85views more  JVCIR 2006»
13 years 7 months ago
Combining geometrical and textured information to perform image classification
In this paper, we propose a framework to carry out supervised classification of images containing both textured and non textured areas. Our approach is based on active contours. U...
Jean-François Aujol, Tony F. Chan
ICIAP
1999
ACM
13 years 11 months ago
Methods for Dynamic Classifier Selection
In the field of pattern recognition, the concept of Multiple Classifier Systems (MCSs) was proposed as a method for the development of high performance classification systems. At ...
Giorgio Giacinto, Fabio Roli