Innovations in Machine Learning Theory and Applications /

• Corporate Author: SpringerLink (Online service)
• Other Authors: Holmes, Dawn E. (Editor), Jain, Lakhmi C. (Editor)
• Format: Electronic eBook
• Language: English
• Published: Berlin, Heidelberg : Springer Berlin Heidelberg, 2006.
• Series: Studies in Fuzziness and Soft Computing, 194
• Subjects: Engineering.; Artificial intelligence.; Applied mathematics.; Engineering mathematics.; Appl.Mathematics/Computational Methods of Engineering.; Artificial Intelligence (incl. Robotics).

Machine learning is currently one of the most rapidly growing areas of research in computer science. In compiling this volume we have brought together contributions from some of the most prestigious researchers in this field. This book covers the three main learning systems; symbolic learning, neura...

Table of Contents:

• A Bayesian Approach to Causal Discovery
• A Tutorial on Learning Causal Influence
• Learning Based Programming
• N-1 Experiments Suffice to Determine the Causal Relations Among N Variables
• Support Vector Inductive Logic Programming
• Neural Probabilistic Language Models
• Computational Grammatical Inference
• On Kernel Target Alignment
• The Structure of Version Space.