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Property testing : a learning theory perspective

Author: Dana Ron
Publisher: Hanover, MA : Now Publishers, ©2008.
Series: Foundations and trends in machine learning
Edition/Format:   eBook : Document : EnglishView all editions and formats
Database:WorldCat
Summary:
Property testing deals with tasks where the goal is to distinguish between the case that an object (e.g., function or graph) has a prespecified property (e.g., the function is linear or the graph is bipartite) and the case that it differs significantly from any such object. The task should be performed by observing only a very small part of the object, in particular by querying the object, and the algorithm is  Read more...
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Genre/Form: Electronic books
Additional Physical Format: Print version:
Ron, Dana.
Property testing.
Hanover, MA : Now Publishers, ©2008
(OCoLC)271432045
Material Type: Document, Internet resource
Document Type: Internet Resource, Computer File
All Authors / Contributors: Dana Ron
ISBN: 9781601981837 160198183X
OCLC Number: 705017332
Description: 1 online resource (ix, 101 pages) : illustrations.
Contents: 1: Introduction 2: Preliminaries 3: Algebraic Properties 4: Basic (Boolean) Function Classes 5: Other Models of Testing 6: Other Results. References. A: The (Multiplicative) Chernoff Bound.
Series Title: Foundations and trends in machine learning
Other Titles: Foundations and trends in machine learning.
Responsibility: Dana Ron.

Abstract:

This survey focuses on results for testing properties of functions that are of interest to the learning theory community.  Read more...

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