CORR
2010
Springer
14 years 16 days ago
2010
Springer
We derive generalization bounds for learning algorithms based on their robustness: the property that if a testing sample is "similar" to a training sample, then the test...
SDM
2007
SIAM
14 years 1 months ago
2007
SIAM
We study a class of algorithms that speed up the training process of support vector machines (SVMs) by returning an approximate SVM. We focus on algorithms that reduce the size of...
NIPS
2007
14 years 1 months ago
2007
The notion of algorithmic stability has been used effectively in the past to derive tight generalization bounds. A key advantage of these bounds is that they are designed for spec...
NIPS
2008
14 years 1 months ago
2008
This work characterizes the generalization ability of algorithms whose predictions are linear in the input vector. To this end, we provide sharp bounds for Rademacher and Gaussian...
ICML
2002
IEEE
15 years 1 months ago
2002
IEEE
We study generalization properties of linear learning algorithms and develop a data dependent approach that is used to derive generalization bounds that depend on the margin distr...
ECCV
2002
Springer
15 years 2 months ago
2002
Springer
Numerous statistical learning methods have been developed for visual recognition tasks. Few attempts, however, have been made to address theoretical issues, and in particular, stud...