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Reliable Reasoning : Induction and Statistical Learning Theory.

By: Contributor(s): Material type: TextTextSeries: Jean Nicod LecturesPublisher: Cambridge : MIT Press, 2007Copyright date: ©2007Edition: 1st edDescription: 1 online resource (119 pages)Content type:
  • text
Media type:
  • computer
Carrier type:
  • online resource
ISBN:
  • 9780262274975
Subject(s): Genre/Form: Additional physical formats: Print version:: Reliable ReasoningDDC classification:
  • 161
LOC classification:
  • BC177.H377 2007
Online resources:
Contents:
Intro -- Contents -- Series Foreword -- Introduction -- 1 - The Problem of Induction -- 2 - Induction and VC Dimension -- 3 - Induction and ''Simplicity'' -- 4 - Neural Networks, Support Vector Machines, and Transduction -- References -- Index.
Summary: The implications for philosophy and cognitive science of developments in statistical learning theory.
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Intro -- Contents -- Series Foreword -- Introduction -- 1 - The Problem of Induction -- 2 - Induction and VC Dimension -- 3 - Induction and ''Simplicity'' -- 4 - Neural Networks, Support Vector Machines, and Transduction -- References -- Index.

The implications for philosophy and cognitive science of developments in statistical learning theory.

Description based on publisher supplied metadata and other sources.

Electronic reproduction. Ann Arbor, Michigan : ProQuest Ebook Central, 2024. Available via World Wide Web. Access may be limited to ProQuest Ebook Central affiliated libraries.

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