James Cussens

According to our database1, James Cussens authored at least 58 papers between 1991 and 2019.

Collaborative distances:
  • Dijkstra number2 of five.
  • Erdős number3 of four.

Timeline

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Links

On csauthors.net:

Bibliography

2019
Finding All Bayesian Network Structures within a Factor of Optimal.
Proceedings of the Thirty-Third AAAI Conference on Artificial Intelligence, 2019

2018
Preface to the special issue on inductive logic programming.
Machine Learning, 2018

Probabilistic logic programming (PLP) 2016.
Int. J. Approx. Reasoning, 2018

Markov Random Field MAP as Set Partitioning.
Proceedings of the International Conference on Probabilistic Graphical Models, 2018

2017
Induction.
Proceedings of the Encyclopedia of Machine Learning and Data Mining, 2017

Polyhedral aspects of score equivalence in Bayesian network structure learning.
Math. Program., 2017

Bayesian Network Structure Learning with Integer Programming: Polytopes, Facets and Complexity.
J. Artif. Intell. Res., 2017

Towards using the chordal graph polytope in learning decomposable models.
Int. J. Approx. Reasoning, 2017

Distributional logic programming for Bayesian knowledge representation.
Int. J. Approx. Reasoning, 2017

Integer Linear Programming for the Bayesian network structure learning problem.
Artif. Intell., 2017

Bayesian Network Structure Learning with Integer Programming: Polytopes, Facets and Complexity (Extended Abstract).
Proceedings of the Twenty-Sixth International Joint Conference on Artificial Intelligence, 2017

2016
Exact estimation of multiple directed acyclic graphs.
Statistics and Computing, 2016

The Chordal Graph Polytope for Learning Decomposable Models.
Proceedings of the Probabilistic Graphical Models - Eighth International Conference, 2016

2015
Introduction to the special issue on probability, logic and learning.
TPLP, 2015

Learning failure-free PRISM programs.
Int. J. Approx. Reasoning, 2015

2013
Advances in Bayesian Network Learning using Integer Programming.
Proceedings of the Twenty-Ninth Conference on Uncertainty in Artificial Intelligence, 2013

2011
Bayesian network learning with cutting planes.
Proceedings of the UAI 2011, 2011

Probabilistic Instruction Cache Analysis Using Bayesian Networks.
Proceedings of the 17th IEEE International Conference on Embedded and Real-Time Computing Systems and Applications, 2011

Online Bayesian Inference for the Parameters of PRISM Programs.
Proceedings of the Inductive Logic Programming - 21st International Conference, 2011

Learning a Generative Failure-Free PRISM Clause.
Proceedings of the Latest Advances in Inductive Logic Programming, 2011

2010
Induction.
Proceedings of the Encyclopedia of Machine Learning, 2010

Approximate Bayesian Computation for the Parameters of PRISM Programs.
Proceedings of the Inductive Logic Programming - 20th International Conference, 2010

Learning Bayesian Networks for Improved Instruction Cache Analysis.
Proceedings of the Ninth International Conference on Machine Learning and Applications, 2010

Maximum likelihood pedigree reconstruction using integer programming.
Proceedings of the Workshop on Constraint Based Methods for Bioinformatics, 2010

Instruction Cache Prediction Using Bayesian Networks.
Proceedings of the ECAI 2010, 2010

2009
Discriminative Clustering for Content-Based Tag Recommendation in Social Bookmarking Systems.
Proceedings of ECML PKDD (The European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases) Discovery Challenge 2009, 2009

Searching a Multivariate Partition Space Using MAX-SAT.
Proceedings of the Computational Intelligence Methods for Bioinformatics and Biostatistics, 2009

2008
Bayesian learning of Bayesian networks with informative priors.
Ann. Math. Artif. Intell., 2008

Bayesian network learning by compiling to weighted MAX-SAT.
Proceedings of the UAI 2008, 2008

CLP(BN): Constraint Logic Programming for Probabilistic Knowledge.
Proceedings of the Probabilistic Inductive Logic Programming - Theory and Applications, 2008

2007
Model equivalence of PRISM programs.
Proceedings of the Probabilistic, Logical and Relational Learning - A Further Synthesis, 15.04., 2007

2006
Inductive Mercury Programming.
Proceedings of the Inductive Logic Programming, 16th International Conference, 2006

2005
Exploiting Informative Priors for Bayesian Classification and Regression Trees.
Proceedings of the IJCAI-05, Proceedings of the Nineteenth International Joint Conference on Artificial Intelligence, Edinburgh, Scotland, UK, July 30, 2005

Tempering for Bayesian C&RT.
Proceedings of the Machine Learning, 2005

Exploiting independence for branch operations in Bayesian learning of C&RTs.
Proceedings of the Probabilistic, Logical and Relational Learning - Towards a Synthesis, 30. January, 2005

2004
At the Interface of Inductive Logic Programming and Statistics.
Proceedings of the Inductive Logic Programming, 14th International Conference, 2004

2003
CLP(BN): Constraint Logic Programming for Probabilistic Knowledge.
Proceedings of the UAI '03, 2003

2002
Issues in Learning Language in Logic.
Proceedings of the Computational Logic: Logic Programming and Beyond, 2002

2001
Parameter Estimation in Stochastic Logic Programs.
Machine Learning, 2001

Markov Chain Monte Carlo using Tree-Based Priors on Model Structure.
Proceedings of the UAI '01: Proceedings of the 17th Conference in Uncertainty in Artificial Intelligence, 2001

Prolog Issues and Experimental Results of an MCMC Algorithm.
Proceedings of the Web Knowledge Management and Decision Support, 2001

Prolog Issues of an MCMC Algorithm.
Proceedings of the 14th International Conference on Applications of Prolog, 2001

Statistical Aspects of Stochastic Logic Programs.
Proceedings of the Eighth International Workshop on Artificial Intelligence and Statistics, 2001

2000
Stochastic Logic Programs: Sampling, Inference and Applications.
Proceedings of the UAI '00: Proceedings of the 16th Conference in Uncertainty in Artificial Intelligence, Stanford University, Stanford, California, USA, June 30, 2000

Incorporating Linguistics Constraints into Inductive Logic Programming.
Proceedings of the Fourth Conference on Computational Natural Language Learning, 2000

1999
Integrating Probabilistic and Logical Reasoning.
Electron. Trans. Artif. Intell., 1999

Loglinear models for first-order probabilistic reasoning.
Proceedings of the UAI '99: Proceedings of the Fifteenth Conference on Uncertainty in Artificial Intelligence, Stockholm, Sweden, July 30, 1999

An Introduction to Inductive Logic Programming and Learning Language in Logic.
Proceedings of the Learning Language in Logic, 1999

Experiments in Inductive Chart Parsing.
Proceedings of the Learning Language in Logic, 1999

Morphosyntactic Tagging of Slovene Using Progol.
Proceedings of the Inductive Logic Programming, 9th International Workshop, 1999

1998
Using Prior Probabilities and Density Estimation for Relational Classification.
Proceedings of the Inductive Logic Programming, 8th International Workshop, 1998

1997
Part-of-Speech Tagging Using Progol.
Proceedings of the Inductive Logic Programming, 7th International Workshop, 1997

1996
Deduction, induction and probabilistic support.
Synthese, 1996

1995
A Bayesian Analysis of Algorithms for Learning Finite Functions.
Proceedings of the Machine Learning, 1995

1993
Bayes and Pseudo-Bayes Estimates of Conditional Probabilities and Their Reliability.
Proceedings of the Machine Learning: ECML-93, 1993

Generating Explicit Orderings for Non-monotonic Logics.
Proceedings of the 11th National Conference on Artificial Intelligence. Washington, 1993

1992
Using Maximum Entropy in a Defeasible Logic with Probabilistic Semantics.
Proceedings of the IPMU '92, 1992

1991
Using Defeasible Logic for a Window on a Probabilistic Database: Some Preliminary Notes.
Proceedings of the Symbolic and Quantitative Approaches to Reasoning and Uncertainty, 1991


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