1427 search results - page 20 / 286 » Learning with Annotation Noise |
ML
2008
ACM
14 years 9 months ago
2008
ACM
In this paper we present the system ALLPAD for learning Logic Programs with Annotated Disjunctions (LPADs). ALLPAD modifies the previous system LLPAD in order to tackle real world ...
66
Voted
ICML
2008
IEEE
15 years 10 months ago
2008
IEEE
A broad class of boosting algorithms can be interpreted as performing coordinate-wise gradient descent to minimize some potential function of the margins of a data set. This class...
COLT
1999
Springer
15 years 1 months ago
1999
Springer
We study the problem of PAC-learning Boolean functions with random attribute noise under the uniform distribution. We define a noisy distance measure for function classes and sho...
73
Voted
STOC
2003
ACM
15 years 10 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...
IPL
2011
14 years 4 months ago
2011
We provide sample complexity of the problem of learning halfspaces with monotonic noise, using the regularized least squares algorithm in the reproducing kernel Hilbert spaces (RKH...