Skip to content
Register Sign in Wishlist

Phase Transitions in Machine Learning

$108.00 (P)

  • Date Published: July 2011
  • availability: In stock
  • format: Hardback
  • isbn: 9780521763912

$ 108.00 (P)

Add to cart Add to wishlist

Other available formats:

Looking for an examination copy?

If you are interested in the title for your course we can consider offering an examination copy. To register your interest please contact providing details of the course you are teaching.

Product filter button
About the Authors
  • Phase transitions typically occur in combinatorial computational problems and have important consequences, especially with the current spread of statistical relational learning as well as sequence learning methodologies. In Phase Transitions in Machine Learning the authors begin by describing in detail this phenomenon, and the extensive experimental investigation that supports its presence. They then turn their attention to the possible implications and explore appropriate methods for tackling them. Weaving together fundamental aspects of computer science, statistical physics and machine learning, the book provides sufficient mathematics and physics background to make the subject intelligible to researchers in AI and other computer science communities. Open research issues are also discussed, suggesting promising directions for future research.

    • Deep analysis of foundational issues in machine learning will interest a variety of readers from outside the field, such as cognitive scientists and philosophers
    • Detailed explanations are aided by examples and applications
    • Suitable textbook for graduate-level courses
    Read more

    Reviews & endorsements

    "... it is still an open question whether this will be one of the basic tools for understanding machine learning problems and methods in the future. Naturally, this book is an essential source for researchers who want to find answers to these questions."
    Joe Hernandez-Orallo, Computing Reviews

    Customer reviews

    Not yet reviewed

    Be the first to review

    Review was not posted due to profanity


    , create a review

    (If you're not , sign out)

    Please enter the right captcha value
    Please enter a star rating.
    Your review must be a minimum of 12 words.

    How do you rate this item?


    Product details

    • Date Published: July 2011
    • format: Hardback
    • isbn: 9780521763912
    • length: 410 pages
    • dimensions: 254 x 195 x 27 mm
    • weight: 1kg
    • contains: 90 b/w illus. 10 tables
    • availability: In stock
  • Table of Contents

    1. Introduction
    2. Statistical physics and phase transitions
    3. The satisfiability problem
    4. Constraint satisfaction problems
    5. Machine learning
    6. Searching the hypothesis space
    7. Statistical physics and machine learning
    8. Learning, SAT, and CSP
    9. Phase transition in FOL covering test
    10. Phase transitions and relational learning
    11. Phase transitions in grammatical inference
    12. Phase transitions in complex systems
    13. Phase transitions in natural systems
    14. Discussions and open issues
    Appendix A. Phase transitions detected in two real cases
    Appendix B. An intriguing idea

  • Authors

    Lorenza Saitta, Università degli Studi del Piemonte Orientale Amedeo Avogadro
    Antoine Cornuéjols is Full Professor of Computer Science at the AgroParisTech Engineering School in Paris.

    Attilio Giordana, Università degli Studi del Piemonte Orientale Amedeo Avogadro
    Attilio Giordana is Full Professor of Computer Science at the University of Piemonte Orientale in Italy.

    Antoine Cornuéjols, AgroParis Tech (INA-PG)
    Lorenza Saitta is a Full Professor of Computer Science at the University of Piemonte Orientale in Italy.

Sign In

Please sign in to access your account


Not already registered? Create an account now. ×

Sorry, this resource is locked

Please register or sign in to request access. If you are having problems accessing these resources please email

Register Sign in
Please note that this file is password protected. You will be asked to input your password on the next screen.

» Proceed

You are now leaving the Cambridge University Press website. Your eBook purchase and download will be completed by our partner Please see the permission section of the catalogue page for details of the print & copy limits on our eBooks.

Continue ×

Continue ×

Continue ×

Find content that relates to you

Join us online

This site uses cookies to improve your experience. Read more Close

Are you sure you want to delete your account?

This cannot be undone.


Thank you for your feedback which will help us improve our service.

If you requested a response, we will make sure to get back to you shortly.

Please fill in the required fields in your feedback submission.