Please note: In order to keep Hive up to date and provide users with the best features, we are no longer able to fully support Internet Explorer. The site is still available to you, however some sections of the site may appear broken. We would encourage you to move to a more modern browser like Firefox, Edge or Chrome in order to experience the site fully.

Phase Transitions in Machine Learning, Hardback Book

Hardback

Description

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.

Information

  • Format:Hardback
  • Pages:410 pages, 10 Tables, black and white; 15 Halftones, unspecified; 75 Line drawings, unspecified
  • Publisher:Cambridge University Press
  • Publication Date:
  • Category:
  • ISBN:9780521763912

£82.99

 
Free Home Delivery

on all orders

 
Pick up orders

from local bookshops

Information

  • Format:Hardback
  • Pages:410 pages, 10 Tables, black and white; 15 Halftones, unspecified; 75 Line drawings, unspecified
  • Publisher:Cambridge University Press
  • Publication Date:
  • Category:
  • ISBN:9780521763912