UAI
2008
13 years 6 months ago
2008
Confidence measures for the generalization error are crucial when small training samples are used to construct classifiers. A common approach is to estimate the generalization err...
NIPS
2007
13 years 6 months ago
2007
Guided by the goal of obtaining an optimization algorithm that is both fast and yields good generalization, we study the descent direction maximizing the decrease in generalizatio...
ICPR
2010
IEEE
13 years 6 months ago
2010
IEEE
A relationship between generalization error and training samples in kernel regressors is discussed in this paper. The generalization error can be decomposed into two components. On...
COLT
2004
Springer
13 years 8 months ago
2004
Springer
We show that forms of Bayesian and MDL inference that are often applied to classification problems can be inconsistent. This means that there exists a learning problem such that fo...
ICIAR
2007
Springer
13 years 8 months ago
2007
Springer
In video-based of face recognition applications, the What-and-Where Fusion Neural Network (WWFNN) has been shown to reduce the generalization error by accumulating a classifier�...
COLT
1992
Springer
13 years 8 months ago
1992
Springer
We propose an algorithm called query by committee, in which a committee of students is trained on the same data set. The next query is chosen according to the principle of maximal...
SSPR
1998
Springer
13 years 8 months ago
1998
Springer
The Pseudo Fisher Linear Discriminant (PFLD) based on a pseudo-inverse technique shows a peaking behaviour of the generalization error for training sample sizes that are about the...
COLT
1998
Springer
13 years 8 months ago
1998
Springer
Most of the work which attempts to give bounds on the generalization error of the hypothesis generated by a learning algorithm is based on methods from the theory of uniform conve...
IWANN
2001
Springer
13 years 9 months ago
2001
Springer
A novel approach to calculate the generalization error of the support vector machines and a new support vector machine–nonsymmatic support vector machine–is proposed here. Our ...
DSMML
2004
Springer
13 years 10 months ago
2004
Springer
Learning curves for Gaussian process (GP) regression can be strongly affected by a mismatch between the ‘student’ model and the ‘teacher’ (true data generation process), e...