11 search results - page 1 / 3 » Rademacher Complexities and Bounding the Excess Risk in Acti... |
JMLR
2010
12 years 11 months ago
2010
Sequential algorithms of active learning based on the estimation of the level sets of the empirical risk are discussed in the paper. Localized Rademacher complexities are used in ...
COLT
2001
Springer
13 years 9 months ago
2001
Springer
We investigate the use of certain data-dependent estimates of the complexity of a function class, called Rademacher and Gaussian complexities. In a decision theoretic setting, we ...
NECO
2010
13 years 3 months ago
2010
In this paper we develop a novel generalization bound for learning the kernel problem. First, we show that the generalization analysis of the kernel learning problem reduces to in...
NIPS
2008
13 years 6 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
2007
IEEE
14 years 5 months ago
2007
IEEE
We propose a formulation of the Decision Tree learning algorithm in the Compression settings and derive tight generalization error bounds. In particular, we propose Sample Compres...