Algebraic Geometry and Statistical Learning Theory Cambridge Monographs on Applied and Computational Mathematics, Series Number 25 1st Edition
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Algebraic Geometry and Statistical Learning Theory Cambridge Monographs on Applied and Computational Mathematics, Series Number 25 1st Edition
Watanabe’s book lays the foundations for the use of algebraic geometry in statistical learning theory.
Algebraic Geometry and Statistical Learning Theory Cambridge Monographs on Applied and Computational Mathematics, Series Number 25 1st Edition
Nº de artículo: 58626472

Algebraic Geometry and Statistical Learning Theory Cambridge Monographs on Applied and Computational Mathematics, Series Number 25 1st Edition

Nº de artículo: 58626472

GTQ 858

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Watanabe’s book lays the foundations for the use of algebraic geometry in statistical learning theory.
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What Stands Out

Interdisciplinary Approach
Combines algebraic geometry and statistical learning theory, offering a unique perspective that bridges mathematics and statistics for advanced learners and researchers.
Comprehensive Coverage
Provides in-depth theoretical insights and practical applications, making complex concepts accessible for graduate students and professionals in applied mathematics.
Renowned Authors
Authored by leading experts in the field, ensuring high-quality content that reflects current trends and research in applied and computational mathematics.

Detalles de producto

Shop Algebraic Geometry and Statistical Learning Theory Cambridge Monographs on Applied and Computational Mathematics, Series Number 25 1st Edition online at a best price in Guatemala. 0521864674
  • Foundational book by Watanabe integrating algebraic geometry into statistical learning theory
  • Addresses singular models/machines such as mixture models, neural networks, HMMs, Bayesian networks, and stochastic context-free grammars
  • Provides theoretical basis for accurate estimation techniques in the presence of singularities
  • Part of the Cambridge Monographs on Applied and Computational Mathematics series
  • Sure to have a significant impact in the field of statistical learning theory
  • First edition of the book
Publisher Cambridge University Press
Publication date September 28, 2009
Edition 1st
Language English
Print length 300 pages
ISBN-10 0521864674
ISBN-13 978-0521864671
Item Weight 1.25 pounds (570 grams)
Dimensions 6.25 x 1 x 9 inches (15.9 x 2.5 x 22.9 cm)

Who Should Buy?

Suitable For
  • Graduate Students

    Ideal for advanced graduate students focusing on the intersection of algebraic geometry and statistical learning theory.

  • Research Professionals

    Useful for researchers seeking to apply algebraic geometry concepts in statistical learning frameworks and computational mathematics.

  • Mathematical Statisticians

    Perfect for statisticians interested in theoretical foundations and mathematical underpinnings of statistical learning algorithms.

Not Suitable For
  • Casual Readers

    Not suitable for casual readers; the content is complex and requires foundational knowledge in mathematics.

  • Undergraduate Students

    Undergraduates may find the material too advanced without prior exposure to algebraic geometry or statistical theory.

  • Practitioners Only

    This book is theoretical and may not cater to practitioners seeking practical applications without mathematical rigor.

DESCRIPCIÓN DEL PRODUCTO

Algebraic Geometry and Statistical Learning Theory Cambridge Monographs on Applied and Computational Mathematics, Series Number 25 1st Edition

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Preguntas y respuestas de los clientes

  • Pregunta: What is the focus of Watanabe's book?

    Respuesta: The book lays the foundations for the use of algebraic geometry in statistical learning theory.
  • Pregunta: What are some examples of singular models/machines?

    Respuesta: Mixture models, neural networks, HMMs, Bayesian networks, stochastic context-free grammars are some of the major examples.
  • Pregunta: What is the usefulness of this book?

    Respuesta: The theory achieved in the book will help in accurate estimation techniques in the presence of singularities.

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GTQ 858

Haz tu pedido ahora y recíbelo por ahí Miércoles, Julio 08

QTY:

Secured transactionsecured transaction

Ubuy works hard to protect your security and privacy. Our advanced payment security system ensures confidentiality by encrypting your information during transmission using AES (Advanced Encryption Standards) and SSL (Secure Socket Layer) protocols. Your payment details are 100% secure as we do not share your payment details with third party sellers.

Our Top Logistics Partners
  • fedex
  • dhl
Fastest cross-border delivery

características y beneficios

  • Algebraic geometry can now be used in statistical learning theory
  • The book focuses on singular models/machines
  • Major examples of such models include mixture models, neural networks, HMMs, Bayesian networks etc.
  • The theory lays the groundwork for accurate estimation in the presence of singularities.