393 search results - page 18 / 79 » On the Convergence of Boosting Procedures |
TNN
2010
13 years 3 months ago
2010
Abstract--Recently, sparse approximation has become a preferred method for learning large scale kernel machines. This technique attempts to represent the solution with only a subse...
TNN
2010
13 years 3 months ago
2010
In recent years, learning from imbalanced data has attracted growing attention from both academia and industry due to the explosive growth of applications that use and produce imba...
ICML
2007
IEEE
14 years 9 months ago
2007
IEEE
Traditional machine learning makes a basic assumption: the training and test data should be under the same distribution. However, in many cases, this identicaldistribution assumpt...
CHARME
2003
Springer
14 years 1 months ago
2003
Springer
We consider the problem of bounded model checking of systems expressed in a decidable fragment of first-order logic. While model checking is not guaranteed to terminate for an ar...
COLT
1997
Springer
14 years 23 days ago
1997
Springer
The problem of learning linear discriminant concepts can be solved by various mistake-driven update procedures, including the Winnow family of algorithms and the well-known Percep...