New Algorithms for Attribute-Efficient on -Line Linear Learning
Harris, Harlan D.
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Permalink
https://hdl.handle.net/2142/81622
Description
Title
New Algorithms for Attribute-Efficient on -Line Linear Learning
Author(s)
Harris, Harlan D.
Issue Date
2003
Doctoral Committee Chair(s)
Gary Dell
Roth, Dan
Department of Study
Computer Science
Discipline
Computer Science
Degree Granting Institution
University of Illinois at Urbana-Champaign
Degree Name
Ph.D.
Degree Level
Dissertation
Keyword(s)
Artificial Intelligence
Language
eng
Abstract
Another significant goal of this work was to identify the inductive biases of each algorithm, so that they can be fairlycompared with each other. By examining their biases and properties using the results presented here, it is possible to view 2Pes as a particular generalization of the Winnow algorithm, and IDBD as a further generalization of 2Pes. Understanding these relationships furthers the potential of attribute-efficient algorithms for real-world applications.
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