Phase Transitions in Machine Learning
Book Details
Format
Hardback or Cased Book
ISBN-10
0521763916
ISBN-13
9780521763912
Publisher
Cambridge University Press
Imprint
Cambridge University Press
Country of Manufacture
GB
Country of Publication
GB
Publication Date
Jun 16th, 2011
Print length
410 Pages
Weight
11 grams
Dimensions
24.80 x 26.50 x 3.00 cms
Product Classification:
Machine learning
Ksh 17,100.00
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0 in stock
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This state-of-the-art overview describes how phase transitions occur and teaches appropriate methods for tackling the consequent problems. Weaving together fundamental aspects of computer science, statistical physics and machine learning, it provides sufficient mathematics and physics background to make the subject intelligible to researchers in AI and other computer science communities.
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.
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