53 search results - page 2 / 11 » On the Existence of Linear Weak Learners and Applications to... |
CVPR
2012
IEEE
11 years 7 months ago
2012
IEEE
The problem of simultaneous feature extraction and selection, for classifier design, is considered. A new framework is proposed, based on boosting algorithms that can either 1) s...
STOC
2003
ACM
14 years 5 months ago
2003
ACM
Boosting algorithms are procedures that "boost" low-accuracy weak learning algorithms to achieve arbitrarily high accuracy. Over the past decade boosting has been widely...
CORR
2011
Springer
12 years 9 months ago
2011
Springer
Boosting is a popular way to derive powerful learners from simpler hypothesis classes. Following previous work (Mason et al., 1999; Friedman, 2000) on general boosting frameworks,...
SIAMSC
2011
13 years 6 days ago
2011
In this paper we describe a general framework for deriving modified equations for stochastic differential equations with respect to weak convergence. Modified equations are deri...
ACL
2008
13 years 6 months ago
2008
Current re-ranking algorithms for machine translation rely on log-linear models, which have the potential problem of underfitting the training data. We present BoostedMERT, a nove...