Probabilistic inductive logic programming. Theory and applications
From MaRDI portal
Publication:2473927
DOI10.1007/978-3-540-78652-8zbMath1132.68007OpenAlexW4255373292MaRDI QIDQ2473927
No author found.
Publication date: 5 March 2008
Published in: Lecture Notes in Computer Science (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1007/978-3-540-78652-8
Learning and adaptive systems in artificial intelligence (68T05) Collections of articles of miscellaneous specific interest (00B15) Proceedings, conferences, collections, etc. pertaining to computer science (68-06) Logic programming (68N17)
Related Items (42)
Lifted generative learning of Markov logic networks ⋮ A survey of lifted inference approaches for probabilistic logic programming under the distribution semantics ⋮ Probabilistic logic programming for hybrid relational domains ⋮ \(T_{\mathcal{P}}\)-compilation for inference in probabilistic logic programs ⋮ Lifted Variable Elimination for Probabilistic Logic Programming ⋮ Infinite probability computation by cyclic explanation graphs ⋮ Exploiting symmetries for scaling loopy belief propagation and relational training ⋮ The effect of combination functions on the complexity of relational Bayesian networks ⋮ Approximate classification with web ontologies through evidential terminological trees and forests ⋮ Introduction to the special issue on probability, logic and learning ⋮ Viterbi training in PRISM ⋮ Structure learning of probabilistic logic programs by searching the clause space ⋮ Inference and learning in probabilistic logic programs using weighted Boolean formulas ⋮ Mining the semantic web statistical learning for next generation knowledge bases ⋮ Stochastic relational processes: efficient inference and applications ⋮ \(\alpha\)ILP: thinking visual scenes as differentiable logic programs ⋮ The joy of probabilistic answer set programming: semantics, complexity, expressivity, inference ⋮ ILP turns 20. Biography and future challenges ⋮ Bridging logic and kernel machines ⋮ Applying the information bottleneck to statistical relational learning ⋮ Fast learning of relational kernels ⋮ Conditional probability logic, lifted Bayesian networks, and almost sure quantifier elimination ⋮ Foundations of Support Constraint Machines ⋮ kLog: a language for logical and relational learning with kernels ⋮ Discriminative Structure Learning of Markov Logic Networks ⋮ MAP Inference for Probabilistic Logic Programming ⋮ Type extension trees for feature construction and learning in relational domains ⋮ Some thoughts on knowledge-enhanced machine learning ⋮ Semantic-based regularization for learning and inference ⋮ Relational linear programming ⋮ Preprocessing for Optimization of Probabilistic-Logic Models for Sequence Analysis ⋮ Speeding up parameter and rule learning for acyclic probabilistic logic programs ⋮ Unnamed Item ⋮ The finite model theory of Bayesian network specifications: descriptive complexity and zero/one laws ⋮ Learning with Kernels and Logical Representations ⋮ Learning probabilistic logic models from probabilistic examples ⋮ Unnamed Item ⋮ Inductive learning of answer set programs for autonomous surgical task planning. Application to a training task for surgeons ⋮ Abduction with probabilistic logic programming under the distribution semantics ⋮ Unnamed Item ⋮ Optimizing Probabilities in Probabilistic Logic Programs ⋮ Lifted graphical models: a survey
This page was built for publication: Probabilistic inductive logic programming. Theory and applications