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» Ensemble Methods in Machine Learning
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EPIA
2003
Springer
15 years 9 months ago
Adaptation to Drifting Concepts
Most of supervised learning algorithms assume the stability of the target concept over time. Nevertheless in many real-user modeling systems, where the data is collected over an ex...
Gladys Castillo, João Gama, Pedro Medas
JMLR
2008
133views more  JMLR 2008»
15 years 4 months ago
Algorithms for Sparse Linear Classifiers in the Massive Data Setting
Classifiers favoring sparse solutions, such as support vector machines, relevance vector machines, LASSO-regression based classifiers, etc., provide competitive methods for classi...
Suhrid Balakrishnan, David Madigan
TIFS
2008
154views more  TIFS 2008»
15 years 4 months ago
Data Fusion and Cost Minimization for Intrusion Detection
Abstract--Statistical pattern recognition techniques have recently been shown to provide a finer balance between misdetections and false alarms than the more conventional intrusion...
Devi Parikh, Tsuhan Chen
BMCBI
2006
159views more  BMCBI 2006»
15 years 4 months ago
EVEREST: automatic identification and classification of protein domains in all protein sequences
Background: Proteins are comprised of one or several building blocks, known as domains. Such domains can be classified into families according to their evolutionary origin. Wherea...
Elon Portugaly, Amir Harel, Nathan Linial, Michal ...
170
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GECCO
2006
Springer
162views Optimization» more  GECCO 2006»
15 years 8 months ago
Evolutionary learning with kernels: a generic solution for large margin problems
In this paper we embed evolutionary computation into statistical learning theory. First, we outline the connection between large margin optimization and statistical learning and s...
Ingo Mierswa