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Autor(en): 
  • Kristian Kersting
  • An Inductive Logic Programming Approach to Statistical Relational Learning 
     

    (Buch)
    Dieser Artikel gilt, aufgrund seiner Grösse, beim Versand als 3 Artikel!


    Übersicht

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    Lieferstatus:   i.d.R. innert 14-24 Tagen versandfertig
    Veröffentlichung:  Oktober 2006  
    Genre:  EDV / Informatik 
    ISBN:  9781586036744 
    EAN-Code: 
    9781586036744 
    Verlag:  IOS Press 
    Einband:  Gebunden  
    Sprache:  English  
    Dimensionen:  H 240 mm / B 161 mm / D 18 mm 
    Gewicht:  554 gr 
    Seiten:  256 
    Zus. Info:  HC gerader Rücken kaschiert 
    Bewertung: Titel bewerten / Meinung schreiben
    Inhalt:
    In his publication, the author Kristian Kersting has made an assault on one of the hardest integration problems at the heart of Artificial Intelligence research. This involves taking three disparate major areas of research and attempting a fusion among them. The three areas are: Logic Programming, Uncertainty Reasoning and Machine Learning. Every one of these is a major sub-area of research with its own associated international research conferences. Having taken on such a Herculean task, Kersting has produced a series of results which are now at the core of a newly emerging area: Probabilistic Inductive Logic Programming. The new area is closely tied to, though strictly subsumes, a new field known as 'Statistical Relational Learning' which has in the last few years gained major prominence in the American Artificial Intelligence research community. Within this book, the author makes several major contributions, including the introduction of a series of definitions which circumscribe the new area formed by extending Inductive Logic Programming to the case in which clauses are annotated with probability values. Also, Kersting investigates the approach of Learning from proofs and the issue of upgrading Fisher Kernels to Relational Fisher kernels.

      



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