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, neural networks and genetic algorithms as well as providing a tutorial on learning casual influences. Each of the nine chapters is self-contained.

Both theoreticians and application scientists/engineers in the broad area of artificial intelligence will find this volume valuable. It also provides a useful sourcebook for Postgraduate since it shows the direction of current research.

Sommario

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.

Riassunto

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, neural networks and genetic algorithms as well as providing a tutorial on learning casual influences. Each of the nine chapters is self-contained.

Both theoreticians and application scientists/engineers in the broad area of artificial intelligence will find this volume valuable. It also provides a useful sourcebook for Postgraduate since it shows the direction of current research.

Dettagli sul prodotto

• Con la collaborazione di: Daw E Holmes (Editore), Dawn E Holmes (Editore), Dawn E. Holmes (Editore), Lakhmi C. Jain (Editore)
• Editore: Springer, Berlin
• Lingue: Inglese
• Formato: Tascabile
• Pubblicazione: 11.10.2010
• EAN: 9783642067884
• ISBN: 978-3-642-06788-4
• Pagine: 276
• Dimensioni: 152 mm x 17 mm x 229 mm
• Peso: 447 g
• Illustrazioni: XVI, 276 p.
• Serie: Studies in Fuzziness and Soft Computing; Studies in Fuzziness and Soft Computing
• Categorie: Scienze naturali, medicina, informatica, tecnica > Tecnica > Tematiche generali, enciclopedie; C, Künstliche Intelligenz, machine learning, Artificial Intelligence, Kernel, Learning, Neural Networks, engineering, intelligence, Programming, Mathematical and Computational Engineering, Engineering mathematics, Applied mathematics, Mathematical and Computational Engineering Applications, logic programming