Titre: Inductive Logic Programming: 14th International Conference, ILP 2004, Porto, Portugal, September 6-8, 2004, Proceedings (Lecture Notes in Computer Science, 3194)
�diteur: Springer
Date de parution: 2004
Langue: anglais
ISBN � 10 chiffres: 3540229418
ISBN � 13 chiffres: 9783540229414
Reliure: Couverture souple
�tat de l'article: New

A propos de ce titre

Synopsis

Invited Papers.- Automated Synthesis of Data Analysis Programs: Learning in Logic.- At the Interface of Inductive Logic Programming and Statistics.- From Promising to Profitable Applications of ILP: A Case Study in Drug Discovery.- Systems Biology: A New Challenge for ILP.- Scaling Up ILP: Experiences with Extracting Relations from Biomedical Text.- Research Papers.- Macro-Operators Revisited in Inductive Logic Programming.- Bottom-Up ILP Using Large Refinement Steps.- On the Effect of Caching in Recursive Theory Learning.- FOIL-D: Efficiently Scaling FOIL for Multi-relational Data Mining of Large Datasets.- Learning an Approximation to Inductive Logic Programming Clause Evaluation.- Learning Ensembles of First-Order Clauses for Recall-Precision Curves: A Case Study in Biomedical Information Extraction.- Automatic Induction of First-Order Logic Descriptors Type Domains from Observations.- On Avoiding Redundancy in Inductive Logic Programming.- Generalization Algorithms for Second-Order Terms.- Circumscription Policies for Induction.- Logical Markov Decision Programs and the Convergence of Logical TD(?).- Learning Goal Hierarchies from Structured Observations and Expert Annotations.- Efficient Evaluation of Candidate Hypotheses in -log.- An Efficient Algorithm for Reducing Clauses Based on Constraint Satisfaction Techniques.- Improving Rule Evaluation Using Multitask Learning.- Learning Logic Programs with Annotated Disjunctions.- A Simulated Annealing Framework for ILP.- Modelling Inhibition in Metabolic Pathways Through Abduction and Induction.- First Order Random Forests with Complex Aggregates.- A Monte Carlo Study of Randomised Restarted Search in ILP.- Addendum.- Learning, Logic, and Probability: A Unified View.

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