Sciweavers

Share
IJCAI
2007

Maximum Margin Coresets for Active and Noise Tolerant Learning

7 years 9 months ago
Maximum Margin Coresets for Active and Noise Tolerant Learning
We study the problem of learning large margin halfspaces in various settings using coresets to show that coresets are a widely applicable tool for large margin learning. A large margin coreset is a subset of the input data sufficient for approximating the true maximum margin solution. In this work, we provide a direct algorithm and analysis for constructing large margin coresets. We show various applications including a novel coreset based analysis of large margin active learning and a polynomial time (in the number of input data and the amount of noise) algorithm for agnostic learning in the presence of outlier noise. We also highlight a simple extension to multi-class classification problems and structured output learning.
Sariel Har-Peled, Dan Roth, Dav Zimak
Added 29 Oct 2010
Updated 29 Oct 2010
Type Conference
Year 2007
Where IJCAI
Authors Sariel Har-Peled, Dan Roth, Dav Zimak
Comments (0)
books