Maximum Margin Coresets for Active and Noise Tolerant Learning

Har-Peled, Sariel; Roth, Dan; Zimak, Dav A.

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https://hdl.handle.net/2142/11268 Copy

Description

Title

Maximum Margin Coresets for Active and Noise Tolerant Learning

Author(s)

• Har-Peled, Sariel
• Roth, Dan
• Zimak, Dav A.

Issue Date

2006-10

Keyword(s)

computer science

Abstract

We study the problem of learning large margin halfspaces in various settings using coresets and 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.

Type of Resource

text

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http://hdl.handle.net/2142/11268

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