Job scheduling strategies for parallel processing: 13th International Workshop, JSSPP 2007, Seattle, WA, USA, June 17, 2007, Revised Papers

The question, how to combine probability and logic with learning, is getting an increased attention in several disciplines such as knowledge representation, reasoning about uncertainty, data mining, and machine learning simulateously. This results in the newly emerging subfield known under the names of statistical relational learning and probabilistic inductive logic programming. This book provides an introduction to the field with an emphasis on the methods based on logic programming principles. It is concerned with formalisms and systems, implementations and applications, as well as with the theory of probabilistic inductive logic programming. The 13 chapters of this state-of-the-art surveystart with an introduction to probabilistic inductive logic programming; moreover the book presents a detailed overview of the most important probabilisticlogic learning formalisms and systems such as relational sequence learning techniques, using kernels with logical representations.

• ISBN: 978-3-540-78698-6
• Editorial: Springer
• Encuadernacion: Rústica
• Páginas: 195
• Fecha Publicación: 01/04/2008
• Nº Volúmenes: 1
• Idioma: Inglés