Application of abductive ILP to learning metabolic network inhibition from temporal data

Authors:
Alireza Tamaddoni-Nezhad;Raphael Chaleil;Antonis Kakas;Stephen Muggleton
Affiliations:
Dept. of Computing, Imperial College, London;Dept. of Biological Sciences, Imperial College, London;Dept. of Computer Science, University of Cyprus, London;Dept. of Computing, Imperial College, London
Venue:
Machine Learning
Year:
2006

Citing 8
Cited 17

Inductive logic programming

New Generation Computing - Selected papers from the international workshop on algorithmic learning theory,1990
Abductive concept learning

New Generation Computing
Induction: Processes of Inference, Learning, and Discovery

Induction: Processes of Inference, Learning, and Discovery
Abduction in Logic Programming

Computational Logic: Logic Programming and Beyond, Essays in Honour of Robert A. Kowalski, Part I
Learning Programs in the Event Calculus

ILP '97 Proceedings of the 7th International Workshop on Inductive Logic Programming
Which Hypotheses Can Be Found with Inverse Entailment?

ILP '97 Proceedings of the 7th International Workshop on Inductive Logic Programming
Using theory completion to learn a robot navigation control program

ILP'02 Proceedings of the 12th international conference on Inductive logic programming
Learning the structure of dynamic probabilistic networks

UAI'98 Proceedings of the Fourteenth conference on Uncertainty in artificial intelligence

Modeling Biological Networks by Action Languages via Answer Set Programming

Constraints
Learning probabilistic logic models from probabilistic examples

Machine Learning
Structured machine learning: the next ten years

Machine Learning
Inferring Regulatory Networks from Time Series Expression Data and Relational Data Via Inductive Logic Programming

Inductive Logic Programming
Brave induction: a logical framework for learning from incomplete information

Machine Learning
Evaluating abductive hypotheses using an EM algorithm on BDDs

IJCAI'09 Proceedings of the 21st international jont conference on Artifical intelligence
SOLAR: An automated deduction system for consequence finding

AI Communications - Practical Aspects of Automated Reasoning
Knowledge based discovery in systems biology using CF-induction

IEA/AIE'07 Proceedings of the 20th international conference on Industrial, engineering, and other applications of applied intelligent systems
Learning probabilistic logic models from probabilistic examples

ILP'07 Proceedings of the 17th international conference on Inductive logic programming
Discovering rules by meta-level abduction

ILP'09 Proceedings of the 19th international conference on Inductive logic programming
Hypothesizing about causal networks with positive and negative effects by meta-level abduction

ILP'10 Proceedings of the 20th international conference on Inductive logic programming
Variation of background knowledge in an industrial application of ILP

ILP'10 Proceedings of the 20th international conference on Inductive logic programming
Variational bayes inference for logic-based probabilistic models on BDDs

ILP'11 Proceedings of the 21st international conference on Inductive Logic Programming
Does multi-clause learning help in real-world applications?

ILP'11 Proceedings of the 21st international conference on Inductive Logic Programming
Machine learning a probabilistic network of ecological interactions

ILP'11 Proceedings of the 21st international conference on Inductive Logic Programming
Completing causal networks by meta-level abduction

Machine Learning
Learning from interpretation transition

Machine Learning

Quantified Score

Hi-index	0.00

Visualization

Abstract

It is well known that many hard tasks considered in machine learning and data mining can be solved in a rather simple and robust way with an instance- and distance-based approach. In this work we present another difficult task: learning, from large numbers ...