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» Combining Methods for Dynamic Multiple Classifier Systems
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ICML
2004
IEEE
16 years 1 months ago
Multiple kernel learning, conic duality, and the SMO algorithm
While classical kernel-based classifiers are based on a single kernel, in practice it is often desirable to base classifiers on combinations of multiple kernels. Lanckriet et al. ...
Francis R. Bach, Gert R. G. Lanckriet, Michael I. ...
111
Voted
DMIN
2006
115views Data Mining» more  DMIN 2006»
15 years 1 months ago
Development of a Multi-Classifier Approach for Multilingual Text Categorization
- Research work related to applying text categorization methods to a monolingual corpus such as English text collections has been well established by several research teams in rece...
Chung-Hong Lee, Hsin-Chang Yang, Ting-Chung Chen, ...
100
Voted
ICPR
2002
IEEE
16 years 1 months ago
Bayesian Networks as Ensemble of Classifiers
Classification of real-world data poses a number of challenging problems. Mismatch between classifier models and true data distributions on one hand and the use of approximate inf...
Ashutosh Garg, Vladimir Pavlovic, Thomas S. Huang
128
Voted
ICPR
2008
IEEE
15 years 7 months ago
Multimodal biometrics management using adaptive score-level combination
This paper presents a new evolutionary approach for adaptive combination of multiple biometrics to dynamically ensure the performance for the desired level of security. The adapti...
Ajay Kumar, Vivek Kanhangad, David Zhang
98
Voted
GECCO
2006
Springer
159views Optimization» more  GECCO 2006»
15 years 4 months ago
Multi-step environment learning classifier systems applied to hyper-heuristics
Heuristic Algorithms (HA) are very widely used to tackle practical problems in operations research. They are simple, easy to understand and inspire confidence. Many of these HAs a...
Javier G. Marín-Blázquez, Sonia Schu...