Inductive logic programming : 22nd International Conference, ILP 2012, Dubrovnik, Croatia, September 17-19, 2012 : revised selected papers
This book constitutes the thoroughly refereed post-proceedings of the 22nd International Conference on Inductive Logic Programming, ILP 2012, held in Dubrovnik, Croatia, in September 2012. The 18 revised full papers were carefully reviewed and selected from 41 submissions. The papers cover the follo...
Wedi'i Gadw mewn:
| Prif Awdur: | |
|---|---|
| Awduron Eraill: | |
| Fformat: | Livre numérique |
| Iaith: | Anglais |
| Cyhoeddwyd: |
Berlin, Heidelberg :
Springer Berlin Heidelberg
2013.
Cham : Springer Nature |
| Cyfres: | Lecture Notes in Artificial Intelligence
7842 |
| Mynediad Ar-lein: | Accès sur la plateforme de l'éditeur (Springer) Accès sur la plateforme Istex Accès Université d'Orléans Accès INSA CVL |
| Nodyn: |
Archives Springer e-books (Licence nationale) Archives Springer e-books (Licence nationale) |
| Autres localisations: | Voir dans le Sudoc |
| Edition sous un autre format: | • Inductive Logic Programming, Texte imprimé, 9783642388118 • Inductive Logic Programming, Texte imprimé, 9783642388132 |
Tabl Cynhwysion:
- A Relational Approach to Tool-Use Learning in Robots
- A Refinement Operator for Inducing Threaded-Variable Clauses
- Propositionalisation of Continuous Attributes beyond Simple Aggregation
- Topic Models with Relational Features for Drug Design
- Pairwise Markov Logic
- Evaluating Inference Algorithms for the Prolog Factor Language
- Polynomial Time Pattern Matching Algorithm for Ordered Graph Patterns
- Fast Parameter Learning for Markov Logic Networks Using Bayes Nets
- Bounded Least General Generalization
- Itemset-Based Variable Construction in Multi-relational Supervised Learning
- A Declarative Modeling Language for Concept Learning in Description Logics
- Identifying Driver s Cognitive Load Using Inductive Logic Programming
- Opening Doors: An Initial SRL Approach
- Probing the Space of Optimal Markov Logic Networks for Sequence Labeling
- What Kinds of Relational Features Are Useful for Statistical Learning?
- Learning Dishonesty
- Heuristic Inverse Subsumption in Full-Clausal Theories
- Learning Unordered Tree Contraction Patterns in Polynomial TimeA Relational Approach to Tool-Use Learning in Robots
- A Refinement Operator for Inducing Threaded-Variable Clauses
- Propositionalisation of Continuous Attributes beyond Simple Aggregation
- Topic Models with Relational Features for Drug Design
- Pairwise Markov Logic
- Evaluating Inference Algorithms for the Prolog Factor Language
- Polynomial Time Pattern Matching Algorithm for Ordered Graph Patterns
- Fast Parameter Learning for Markov Logic Networks Using Bayes Nets
- Bounded Least General Generalization
- Itemset-Based Variable Construction in Multi-relational Supervised Learning
- A Declarative Modeling Language for Concept Learning in Description Logics
- Identifying Driver s Cognitive Load Using Inductive Logic Programming
- Opening Doors: An Initial SRL Approach
- Probing the Space of Optimal Markov Logic Networks for Sequence Labeling
- What Kinds of Relational Features Are Useful for StatisticalLearning?.-Learning Dishonesty.-Heuristic Inverse Subsumption in Full-Clausal Theories.-Learning Unordered Tree Contraction Patterns in Polynomial Time.