11 search results - page 1 / 3 » Tight Sample Complexity of Large-Margin Learning |
CORR
2010
Springer
13 years 5 months ago
2010
Springer
We obtain a tight distribution-specific characterization of the sample complexity of large-margin classification with L2 regularization: We introduce the -adapted-dimension, which...
PAMI
2010
13 years 3 months ago
2010
—This paper considers feature selection for data classification in the presence of a huge number of irrelevant features. We propose a new feature selection algorithm that addres...
TCC
2010
Springer
14 years 1 months ago
2010
Springer
Learning is a task that generalizes many of the analyses that are applied to collections of data, and in particular, collections of sensitive individual information. Hence, it is n...
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...
ALT
2001
Springer
13 years 9 months ago
2001
Springer
We develop a theory for learning scenarios where multiple learners co-exist but there are mutual compatibility constraints on their outcomes. This is natural in cognitive learning...