The uncertain reasoner's companion: a mathematical perspective
The uncertain reasoner's companion: a mathematical perspective
Convex Optimization
Combining probabilistic logic programming with the power of maximum entropy
Artificial Intelligence - Special issue on nonmonotonic reasoning
Introduction to Statistical Relational Learning (Adaptive Computation and Machine Learning)
Introduction to Statistical Relational Learning (Adaptive Computation and Machine Learning)
First-order probabilistic inference
IJCAI'03 Proceedings of the 18th international joint conference on Artificial intelligence
Lifted first-order probabilistic inference
IJCAI'05 Proceedings of the 19th international joint conference on Artificial intelligence
Conditionals in nonmonotonic reasoning and belief revision: considering conditionals as agents
Conditionals in nonmonotonic reasoning and belief revision: considering conditionals as agents
Probabilistic inductive logic programming
Probabilistic inductive logic programming
Stochastic Relaxation, Gibbs Distributions, and the Bayesian Restoration of Images
IEEE Transactions on Pattern Analysis and Machine Intelligence
SUM'12 Proceedings of the 6th international conference on Scalable Uncertainty Management
JELIA'12 Proceedings of the 13th European conference on Logics in Artificial Intelligence
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For relational probabilistic conditionals, the so-called aggregation semantics has been proposed recently. Applying the maximum entropy principle for reasoning under aggregation semantics requires solving a complex optimization problem. Here, we improve an approach to solving this optimization problem by Generalized Iterative Scaling (GIS). After showing how the method of Lagrange multipliers can also be used for aggregation semantics, we exploit that possible worlds are structurally equivalent with respect to a knowledge base $\mathcal R$ if they have the same verification and falsification properties. We present a GIS algorithm operating on the induced equivalence classes of worlds; its implementation yields significant performance improvements.