Deprecated: $wgMWOAuthSharedUserIDs=false is deprecated, set $wgMWOAuthSharedUserIDs=true, $wgMWOAuthSharedUserSource='local' instead [Called from MediaWiki\HookContainer\HookContainer::run in /var/www/html/w/includes/HookContainer/HookContainer.php at line 135] in /var/www/html/w/includes/Debug/MWDebug.php on line 372
Probabilistic inductive logic programming. Theory and applications - MaRDI portal

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




Related Items (42)

Lifted generative learning of Markov logic networksA survey of lifted inference approaches for probabilistic logic programming under the distribution semanticsProbabilistic logic programming for hybrid relational domains\(T_{\mathcal{P}}\)-compilation for inference in probabilistic logic programsLifted Variable Elimination for Probabilistic Logic ProgrammingInfinite probability computation by cyclic explanation graphsExploiting symmetries for scaling loopy belief propagation and relational trainingThe effect of combination functions on the complexity of relational Bayesian networksApproximate classification with web ontologies through evidential terminological trees and forestsIntroduction to the special issue on probability, logic and learningViterbi training in PRISMStructure learning of probabilistic logic programs by searching the clause spaceInference and learning in probabilistic logic programs using weighted Boolean formulasMining the semantic web statistical learning for next generation knowledge basesStochastic relational processes: efficient inference and applications\(\alpha\)ILP: thinking visual scenes as differentiable logic programsThe joy of probabilistic answer set programming: semantics, complexity, expressivity, inferenceILP turns 20. Biography and future challengesBridging logic and kernel machinesApplying the information bottleneck to statistical relational learningFast learning of relational kernelsConditional probability logic, lifted Bayesian networks, and almost sure quantifier eliminationFoundations of Support Constraint MachineskLog: a language for logical and relational learning with kernelsDiscriminative Structure Learning of Markov Logic NetworksMAP Inference for Probabilistic Logic ProgrammingType extension trees for feature construction and learning in relational domainsSome thoughts on knowledge-enhanced machine learningSemantic-based regularization for learning and inferenceRelational linear programmingPreprocessing for Optimization of Probabilistic-Logic Models for Sequence AnalysisSpeeding up parameter and rule learning for acyclic probabilistic logic programsUnnamed ItemThe finite model theory of Bayesian network specifications: descriptive complexity and zero/one lawsLearning with Kernels and Logical RepresentationsLearning probabilistic logic models from probabilistic examplesUnnamed ItemInductive learning of answer set programs for autonomous surgical task planning. Application to a training task for surgeonsAbduction with probabilistic logic programming under the distribution semanticsUnnamed ItemOptimizing Probabilities in Probabilistic Logic ProgramsLifted graphical models: a survey




This page was built for publication: Probabilistic inductive logic programming. Theory and applications