Foundations of logic programming; (2nd extended ed.)
Foundations of logic programming; (2nd extended ed.)
Inducing Features of Random Fields
IEEE Transactions on Pattern Analysis and Machine Intelligence
Answering queries from context-sensitive probabilistic knowledge bases
Selected papers from the international workshop on Uncertainty in databases and deductive systems
The independent choice logic for modelling multiple agents under uncertainty
Artificial Intelligence - Special issue on economic principles of multi-agent systems
Probabilistic frame-based systems
AAAI '98/IAAI '98 Proceedings of the fifteenth national/tenth conference on Artificial intelligence/Innovative applications of artificial intelligence
Statistical Language Learning
Learning Probabilistic Relational Models
IJCAI '99 Proceedings of the Sixteenth International Joint Conference on Artificial Intelligence
Stochastic Logic Programs: Sampling, Inference and Applications
UAI '00 Proceedings of the 16th Conference on Uncertainty in Artificial Intelligence
Probabilistic First-Order Classification
ILP '97 Proceedings of the 7th International Workshop on Inductive Logic Programming
Maximum Entropy Modeling with Clausal Constraints
ILP '97 Proceedings of the 7th International Workshop on Inductive Logic Programming
Stochastic attribute-value grammars
Computational Linguistics
An Investigation of the Laws of Thought
An Investigation of the Laws of Thought
Learning probabilities for noisy first-order rules
IJCAI'97 Proceedings of the Fifteenth international joint conference on Artifical intelligence - Volume 2
Loglinear models for first-order probabilistic reasoning
UAI'99 Proceedings of the Fifteenth conference on Uncertainty in artificial intelligence
Issues in Learning Language in Logic
Computational Logic: Logic Programming and Beyond, Essays in Honour of Robert A. Kowalski, Part II
Statistical Abduction with Tabulation
Computational Logic: Logic Programming and Beyond, Essays in Honour of Robert A. Kowalski, Part II
Adaptive Bayesian Logic Programs
ILP '01 Proceedings of the 11th International Conference on Inductive Logic Programming
Towards Combining Inductive Logic Programming with Bayesian Networks
ILP '01 Proceedings of the 11th International Conference on Inductive Logic Programming
ACM SIGKDD Explorations Newsletter
Naive Bayesian Classification of Structured Data
Machine Learning
Reading comprehension tests for computer-based understanding evaluation
Natural Language Engineering
Diagnosis using a first-order stochastic language that learns
Expert Systems with Applications: An International Journal
Representing Uncertainty in RuleML
Fundamenta Informaticae
Learning probabilistic logic models from probabilistic examples
Machine Learning
Structured machine learning: the next ten years
Machine Learning
A glimpse of symbolic-statistical modeling by PRISM
Journal of Intelligent Information Systems
Multi-class Prediction Using Stochastic Logic Programs
Inductive Logic Programming
Logic and the Automatic Acquisition of Scientific Knowledge: An Application to Functional Genomics
Computational Discovery of Scientific Knowledge
A Survey of Formal Verification for Business Process Modeling
ICCS '08 Proceedings of the 8th international conference on Computational Science, Part II
A Statistical Approach to Incremental Induction of First-Order Hierarchical Knowledge Bases
ILP '08 Proceedings of the 18th international conference on Inductive Logic Programming
Parameter Learning in Probabilistic Databases: A Least Squares Approach
ECML PKDD '08 Proceedings of the 2008 European Conference on Machine Learning and Knowledge Discovery in Databases - Part I
A methodology for in-network evaluation of integrated logical-statistical models
Proceedings of the 6th ACM conference on Embedded network sensor systems
An Inductive Logic Programming Approach to Statistical Relational Learning
Proceedings of the 2005 conference on An Inductive Logic Programming Approach to Statistical Relational Learning
Bayesian learning of Bayesian networks with informative priors
Annals of Mathematics and Artificial Intelligence
ICLP '09 Proceedings of the 25th International Conference on Logic Programming
Logic-Statistic Models with Constraints for Biological Sequence Analysis
ICLP '09 Proceedings of the 25th International Conference on Logic Programming
Towards learning stochastic logic programs from proof-banks
AAAI'05 Proceedings of the 20th national conference on Artificial intelligence - Volume 2
Parameter learning of logic programs for symbolic-statistical modeling
Journal of Artificial Intelligence Research
View learning for statistical relational learning: with an application to mammography
IJCAI'05 Proceedings of the 19th international joint conference on Artificial intelligence
Generative modeling with failure in PRISM
IJCAI'05 Proceedings of the 19th international joint conference on Artificial intelligence
Learning structure and parameters of stochastic logic programs
ILP'02 Proceedings of the 12th international conference on Inductive logic programming
A hybrid symbolic-statistical approach to modeling metabolic networks
KES'07/WIRN'07 Proceedings of the 11th international conference, KES 2007 and XVII Italian workshop on neural networks conference on Knowledge-based intelligent information and engineering systems: Part I
Learning probabilistic logic models from probabilistic examples
ILP'07 Proceedings of the 17th international conference on Inductive logic programming
Probabilistic inductive logic programming
Probabilistic inductive logic programming
New advances in logic-based probabilistic modeling by PRISM
Probabilistic inductive logic programming
Basic principles of learning Bayesian logic programs
Probabilistic inductive logic programming
Protein fold discovery using stochastic logic programs
Probabilistic inductive logic programming
A behavioral comparison of some probabilistic logic models
Probabilistic inductive logic programming
Learning the parameters of probabilistic logic programs from interpretations
ECML PKDD'11 Proceedings of the 2011 European conference on Machine learning and knowledge discovery in databases - Volume Part I
Bootstrapping parameter estimation in dynamic systems
DS'11 Proceedings of the 14th international conference on Discovery science
Stochastic logic programs: sampling, inference and applications
UAI'00 Proceedings of the Sixteenth conference on Uncertainty in artificial intelligence
Markov chain monte carlo using tree-based priors on model structure
UAI'01 Proceedings of the Seventeenth conference on Uncertainty in artificial intelligence
Toward robust real-world inference: a new perspective on explanation-based learning
ECML'06 Proceedings of the 17th European conference on Machine Learning
Combining bayesian networks with higher-order data representations
IDA'05 Proceedings of the 6th international conference on Advances in Intelligent Data Analysis
Computing confidence measures in stochastic logic programs
MICAI'05 Proceedings of the 4th Mexican international conference on Advances in Artificial Intelligence
Negation elimination for finite PCFGs
LOPSTR'04 Proceedings of the 14th international conference on Logic Based Program Synthesis and Transformation
Logical bayesian networks and their relation to other probabilistic logical models
ILP'05 Proceedings of the 15th international conference on Inductive Logic Programming
Modelling metabolic pathways using stochastic logic programs-based ensemble methods
CMSB'04 Proceedings of the 20 international conference on Computational Methods in Systems Biology
Representing Uncertainty in RuleML
Fundamenta Informaticae
Extending and formalizing bayesian networks by strong relevant logic
ACIIDS'13 Proceedings of the 5th Asian conference on Intelligent Information and Database Systems - Volume Part I
Programming with personalized pagerank: a locally groundable first-order probabilistic logic
Proceedings of the 22nd ACM international conference on Conference on information & knowledge management
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Stochastic logic programs (SLPs) are logic programs with parameterised clauses which define a log-linear distribution over refutations of goals. The log-linear distribution provides, by marginalisation, a distribution over variable bindings, allowing SLPs to compactly represent quite complex distributions.We analyse the fundamental statistical properties of SLPs addressing issues concerning infinite derivations, ‘unnormalised’ SLPs and impure SLPs. After detailing existing approaches to parameter estimation for log-linear models and their application to SLPs, we present a new algorithm called failure-adjusted maximisation (FAM). FAM is an instance of the EM algorithm that applies specifically to normalised SLPs and provides a closed-form for computing parameter updates within an iterative maximisation approach. We empirically show that FAM works on some small examples and discuss methods for applying it to bigger problems.