TEC
2012
12 years 3 months ago
2012
Recently, the generalization framework in co-evolutionary learning has been theoretically formulated and demonstrated in the context of game-playing. Generalization performance of...
ML
2012
ACM
12 years 8 months ago
2012
ACM
Bayesian learning, widely used in many applied data-modeling problems, is often accomplished with approximation schemes because it requires intractable computation of the posterio...
EMNLP
2011
13 years 9 days ago
2011
We consider the problem of learning factored probabilistic CCG grammars for semantic parsing from data containing sentences paired with logical-form meaning representations. Tradi...
CDC
2010
IEEE
13 years 4 months ago
2010
IEEE
—In this paper we study the overparametrization scheme for Hammerstein systems [1] in the presence of regularization. The quality of the convex approximation is analysed, that is...
TIT
1998
14 years 6 days ago
1998
The paper introduces some generalizations of Vapnik’s method of structural risk minimisation (SRM). As well as making explicit some of the details on SRM, it provides a result t...
INFORMATICALT
2000
14 years 11 days ago
2000
An estimation of the generalization performance of classifier is one of most important problems in pattern clasification and neural network training theory. In this paper we estima...
TEC
2008
14 years 14 days ago
2008
Coevolutionary learning involves a training process where training samples are instances of solutions that interact strategically to guide the evolutionary (learning) process. One ...
CSDA
2007
14 years 16 days ago
2007
The problem of choosing a good parameter setting for a better generalization performance in a learning task is the so-called model selection. A nested uniform design (UD) methodol...
NIPS
2001
14 years 1 months ago
2001
We investigate the generalization performance of some learning problems in Hilbert functional Spaces. We introduce a notion of convergence of the estimated functional predictor to...
COLT
2000
Springer
14 years 4 months ago
2000
Springer
This paper collects together a miscellany of results originally motivated by the analysis of the generalization performance of the “maximum-margin” algorithm due to Vapnik and...