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» Evaluating learning algorithms and classifiers
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CVPR
2007
IEEE
15 years 10 months ago
Matrix-Structural Learning (MSL) of Cascaded Classifier from Enormous Training Set
Aiming at the problem when both positive and negative training set are enormous, this paper proposes a novel Matrix-Structural Learning (MSL) method, as an extension to Viola and ...
Shengye Yan, Shiguang Shan, Xilin Chen, Wen Gao, J...
JMLR
2010
129views more  JMLR 2010»
14 years 10 months ago
Learning Polyhedral Classifiers Using Logistic Function
In this paper we propose a new algorithm for learning polyhedral classifiers. In contrast to existing methods for learning polyhedral classifier which solve a constrained optimiza...
Naresh Manwani, P. S. Sastry
ICML
2003
IEEE
16 years 4 months ago
Margin Distribution and Learning
Recent theoretical results have shown that improved bounds on generalization error of classifiers can be obtained by explicitly taking the observed margin distribution of the trai...
Ashutosh Garg, Dan Roth
GECCO
2006
Springer
159views Optimization» more  GECCO 2006»
15 years 7 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...
ICDAR
2009
IEEE
15 years 1 months ago
Learning Bayesian Networks by Evolution for Classifier Combination
Combining classifier methods have shown their effectiveness in a number of applications. Nonetheless, using simultaneously multiple classifiers may result in some cases in a reduc...
Claudio De Stefano, Francesco Fontanella, Alessand...