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Science/Engineering Statistical Mechanics, Third Edition
Science/Engineering Essentials of Toxic Chemical Risk: Science and Society
Science/Engineering Telefoncoaching: So machen Sie aus Ihren Mitarbeitern Telefonprofis
Science/Engineering Wireless Communications (Wiley - IEEE)
Science/Engineering Posttraumatische Belastungsstörungen (German Edition)
Science/Engineering Lernplattformen in Schulen: Ansätze für E-Learning und Blended Learning in Präsenzklassen (1 Auflage)
Science/Engineering Stochastik für Einsteiger: Eine Einführung in die faszinierende Welt des Zufalls. Mit über 220 Übungsaufgaben und Lösungen {Repost}
Science/Engineering Testtheorie und Fragebogenkonstruktion (Springer-Lehrbuch)
Science/Engineering Centrifugal Pumps, 2nd Edition
Science/Engineering Computational Intelligence for Modelling and Prediction (Studies in Computational Intelligence) 1 edition {Repost}
Science/Engineering Networks, Crowds, and Markets: Reasoning About a Highly Connected World {repost}
Science/Engineering Introduction to Biophotonics (repost)
Science/Engineering The Art and Science of Psychotherapy (repost)
Science/Engineering Advances in Chemical Physics - Volume 15: Stochastic Processes in Chemical Physics
Science/Engineering "Emulsion Science: Basic Principles" (repost)
Science/Engineering Elementary Principles of Chemical Processes 3rd edition
Science/Engineering Boundary Element Analysis (repost)
Science/Engineering Collection of books on physics 2
Science/Engineering A Practical Handbook of Preparative HPLC by Donald A. Wellings (Repost)
Science/Engineering Reviews of Environmental Contamination and Toxicology 184 by George W. Ware
Science/Engineering Essentials of Toxic Chemical Risk: Science and Society
Science/Engineering Telefoncoaching: So machen Sie aus Ihren Mitarbeitern Telefonprofis
Science/Engineering Wireless Communications (Wiley - IEEE)
Science/Engineering Posttraumatische Belastungsstörungen (German Edition)
Science/Engineering Lernplattformen in Schulen: Ansätze für E-Learning und Blended Learning in Präsenzklassen (1 Auflage)
Science/Engineering Stochastik für Einsteiger: Eine Einführung in die faszinierende Welt des Zufalls. Mit über 220 Übungsaufgaben und Lösungen {Repost}
Science/Engineering Testtheorie und Fragebogenkonstruktion (Springer-Lehrbuch)
Science/Engineering Centrifugal Pumps, 2nd Edition
Science/Engineering Computational Intelligence for Modelling and Prediction (Studies in Computational Intelligence) 1 edition {Repost}
Science/Engineering Networks, Crowds, and Markets: Reasoning About a Highly Connected World {repost}
Science/Engineering Introduction to Biophotonics (repost)
Science/Engineering The Art and Science of Psychotherapy (repost)
Science/Engineering Advances in Chemical Physics - Volume 15: Stochastic Processes in Chemical Physics
Science/Engineering "Emulsion Science: Basic Principles" (repost)
Science/Engineering Elementary Principles of Chemical Processes 3rd edition
Science/Engineering Boundary Element Analysis (repost)
Science/Engineering Collection of books on physics 2
Science/Engineering A Practical Handbook of Preparative HPLC by Donald A. Wellings (Repost)
Science/Engineering Reviews of Environmental Contamination and Toxicology 184 by George W. Ware
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Science/Engineering Introduction to Statistical Relational Learning
Posted on 2010-03-15
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More Lise Getoor, Ben Taskar “Introduction to Statistical Relational Learning" Handling inherent uncertainty and exploiting compositional structure are fundamental to understanding and designing large-scale systems. Statistical relational learning builds on ideas from probability theory and statistics to address uncertainty while incorporating tools from logic, databases, and programming languages to represent structure. In Introduction to Statistical Relational Learning, leading researchers in this emerging area of machine learning describe current formalisms, models, and algorithms that enable effective and robust reasoning about richly structured systems and data. The early chapters provide tutorials for material used in later chapters, offering introductions to representation, inference and learning in graphical models, and logic. The book then describes object-oriented approaches, including probabilistic relational models, relational Markov networks, and probabilistic entity-relationship models as well as logic-based formalisms including Bayesian logic programs, Markov logic, and stochastic logic programs. Later chapters discuss such topics as probabilistic models with unknown objects, relational dependency networks, reinforcement learning in relational domains, and information extraction. By presenting a variety of approaches, the book highlights commonalities and clarifies important differences among proposed approaches and, along the way, identifies important representational and algorithmic issues. Numerous applications are provided throughout. "
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