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» An Empirical Study of Regression Test Selection Techniques
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ESWA
2007
100views more  ESWA 2007»
13 years 9 months ago
Treatment of multi-dimensional data to enhance neural network estimators in regression problems
This paper proposes and explains a data treatment technique to improve the accuracy of a neural network estimator in regression problems, where multi-dimensional input data set is...
H. Altun, A. Bilgil, B. C. Fidan
ICRA
2008
IEEE
150views Robotics» more  ICRA 2008»
14 years 3 months ago
A Bayesian approach to empirical local linearization for robotics
— Local linearizations are ubiquitous in the control of robotic systems. Analytical methods, if available, can be used to obtain the linearization, but in complex robotics system...
Jo-Anne Ting, Aaron D'Souza, Sethu Vijayakumar, St...
NIPS
2004
13 years 10 months ago
Computing regularization paths for learning multiple kernels
The problem of learning a sparse conic combination of kernel functions or kernel matrices for classification or regression can be achieved via the regularization by a block 1-norm...
Francis R. Bach, Romain Thibaux, Michael I. Jordan
ICONIP
2004
13 years 10 months ago
Hybrid Feature Selection for Modeling Intrusion Detection Systems
Most of the current Intrusion Detection Systems (IDS) examine all data features to detect intrusion or misuse patterns. Some of the features may be redundant or contribute little (...
Srilatha Chebrolu, Ajith Abraham, Johnson P. Thoma...
ISSRE
2008
IEEE
14 years 3 months ago
Finding Faults: Manual Testing vs. Random+ Testing vs. User Reports
The usual way to compare testing strategies, whether theoretically or empirically, is to compare the number of faults they detect. To ascertain definitely that a testing strategy...
Ilinca Ciupa, Bertrand Meyer, Manuel Oriol, Alexan...