Innovations in Machine Learning Theory and Applications /

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...

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Detalles Bibliográficos
Clasificación:Libro Electrónico
Autor Corporativo: SpringerLink (Online service)
Otros Autores: Holmes, Dawn E. (Editor )
Formato: Electrónico eBook
Idioma:Inglés
Publicado: Berlin, Heidelberg : Springer Berlin Heidelberg : Imprint: Springer, 2006.
Edición:1st ed. 2006.
Colección:Studies in Fuzziness and Soft Computing, 194
Temas:
Engineering mathematics.
Engineering-Data processing.
Artificial intelligence.
Mathematical and Computational Engineering Applications.
Artificial Intelligence.
Acceso en línea:Texto Completo
Tabla de Contenidos:
  • 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.

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