List of Figures Contributors Preface I OVERVIEW 1 Statistical Relational AI: Representation, Inference and Learning 2 Modeling and Reasoning with Statistical Relational Representation 3 Statistical Relational Learning II EXACT INFERENCE 4 Lifted Variable Elimination 5 Search-Based Exact Lifted Inference 6 Lifted Aggregation and Skolemization for Directed Models 7 First-Order Knowledge Compilation 8 Domain Liftability 9 Tractability through Exchangeability: The Statistics of Lifting III APPROXIMATE INFERENCE 10 Lifted Markov Chain Monte Carlo 11 Lifted Message Passing for Probabilistic and Combinatorial Problems 12 Lifted Generalized Belief Propagation: Relax, Compensate and Recover 13 Liftability Theory of Variational Inference 14 Lifted Inference for Hybrid Relational Models IV BEYOND PROBABILISTIC INFERENCE 15 Color Refinement and Its Applications 16 Stochastic Planning and Lifted Inference Bibliography Index
Guy Van den Broeck is Associate Professor of Computer Science at the University of California, Los Angeles. Kristian Kersting is Professor in the Computer Science Department and the Centre for Cognitive Science at Technische Universität Darmstadt. Sriraam Natarajan is Professor and the Director of the Center for Machine Learning in the Department of Computer Science at University of Texas at Dallas. David Poole is Professor in the Department of Computer Science at the University of British Columbia.