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IJCAI
2007

Maximum Margin Coresets for Active and Noise Tolerant Learning

7 years 11 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
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