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ICNC
2005
Springer
15 years 11 months ago
Training Data Selection for Support Vector Machines
Abstract. In recent years, support vector machines (SVMs) have become a popular tool for pattern recognition and machine learning. Training a SVM involves solving a constrained qua...
Jigang Wang, Predrag Neskovic, Leon N. Cooper
CEC
2010
IEEE
15 years 7 months ago
Two novel Ant Colony Optimization approaches for Bayesian network structure learning
Learning Bayesian networks from data is an N-P hard problem with important practical applications. Several researchers have designed algorithms to overcome the computational comple...
Yanghui Wu, John A. W. McCall, David W. Corne
COLT
2008
Springer
15 years 8 months ago
Adaptive Hausdorff Estimation of Density Level Sets
Consider the problem of estimating the -level set G = {x : f(x) } of an unknown d-dimensional density function f based on n independent observations X1, . . . , Xn from the densi...
Aarti Singh, Robert Nowak, Clayton Scott
ESANN
2004
15 years 7 months ago
Sparse LS-SVMs using additive regularization with a penalized validation criterion
This paper is based on a new way for determining the regularization trade-off in least squares support vector machines (LS-SVMs) via a mechanism of additive regularization which ha...
Kristiaan Pelckmans, Johan A. K. Suykens, Bart De ...
IJCAI
1989
15 years 7 months ago
Selective Learning of Macro-operators with Perfect Causality
A macro-operator is an integrated operator consisting of plural primitive operators and enables a problem solver to solve more efficiently. However, if a learning system generates...
Seiji Yamada, Sabinro Tsuji