James Cussens

According to our database, James Cussens authored at least 70 papers between 1991 and 2023.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2023

Branch-Price-and-Cut for Causal Discovery.

James Cussens

Proceedings of the Conference on Causal Learning and Reasoning, 2023

2021

The dual polyhedron to the chordal graph polytope and the rebuttal of the chordal graph conjecture.

Milan Studený, James Cussens, Václav Kratochvíl

Int. J. Approx. Reason., 2021

2020

Learning All Credible Bayesian Network Structures for Model Averaging.

Zhenyu A. Liao, Charupriya Sharma, James Cussens, Peter van Beek

CoRR, 2020

Dual Formulation of the Chordal Graph Conjecture.

Milan Studený, James Cussens, Václav Kratochvíl

Proceedings of the International Conference on Probabilistic Graphical Models, 2020

A Score-and-Search Approach to Learning Bayesian Networks with Noisy-OR Relations.

Charupriya Sharma, Zhenyu A. Liao, James Cussens, Peter van Beek

Proceedings of the International Conference on Probabilistic Graphical Models, 2020

Kernel-based Approach for Learning Causal Graphs from Mixed Data.

Teny Handhayani, James Cussens

Proceedings of the International Conference on Probabilistic Graphical Models, 2020

GOBNILP: Learning Bayesian network structure with integer programming.

James Cussens

Proceedings of the International Conference on Probabilistic Graphical Models, 2020

On Pruning for Score-Based Bayesian Network Structure Learning.

Alvaro Henrique Chaim Correia, James Cussens, Cassio P. de Campos

Proceedings of the 23rd International Conference on Artificial Intelligence and Statistics, 2020

2019

Kernel-based Approach to Handle Mixed Data for Inferring Causal Graphs.

Teny Handhayani, James Cussens

CoRR, 2019

Online Causal Structure Learning in the Presence of Latent Variables.

Durdane Kocacoban, James Cussens

Proceedings of the 18th IEEE International Conference On Machine Learning And Applications, 2019

Finding All Bayesian Network Structures within a Factor of Optimal.

Zhenyu A. Liao, Charupriya Sharma, James Cussens, Peter van Beek

Proceedings of the Thirty-Third AAAI Conference on Artificial Intelligence, 2019

2018

Preface to the special issue on inductive logic programming.

James Cussens, Alessandra Russo

Mach. Learn., 2018

Probabilistic logic programming (PLP) 2016.

Arjen Hommersom, James Cussens

Int. J. Approx. Reason., 2018

Finding Minimal Cost Herbrand Models with Branch-Cut-and-Price.

James Cussens

CoRR, 2018

Markov Random Field MAP as Set Partitioning.

James Cussens

Proceedings of the International Conference on Probabilistic Graphical Models, 2018

2017

Induction.

James Cussens

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

Polyhedral aspects of score equivalence in Bayesian network structure learning.

James Cussens, David Haws, Milan Studený

Math. Program., 2017

Bayesian Network Structure Learning with Integer Programming: Polytopes, Facets and Complexity.

James Cussens, Matti Järvisalo, Janne H. Korhonen, Mark Bartlett

J. Artif. Intell. Res., 2017

Towards using the chordal graph polytope in learning decomposable models.

Milan Studený, James Cussens

Int. J. Approx. Reason., 2017

Distributional logic programming for Bayesian knowledge representation.

Nicos Angelopoulos, James Cussens

Int. J. Approx. Reason., 2017

Integer Linear Programming for the Bayesian network structure learning problem.

Mark Bartlett, James Cussens

Artif. Intell., 2017

Bayesian Network Structure Learning with Integer Programming: Polytopes, Facets and Complexity (Extended Abstract).

James Cussens, Matti Järvisalo, Janne H. Korhonen, Mark Bartlett

Proceedings of the Twenty-Sixth International Joint Conference on Artificial Intelligence, 2017

2016

Exact estimation of multiple directed acyclic graphs.

Chris J. Oates, Jim Q. Smith, Sach Mukherjee, James Cussens

Stat. Comput., 2016

The Chordal Graph Polytope for Learning Decomposable Models.

Milan Studený, James Cussens

Proceedings of the Probabilistic Graphical Models - Eighth International Conference, 2016

2015

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

James Cussens, Luc De Raedt, Angelika Kimmig, Taisuke Sato

Theory Pract. Log. Program., 2015

Learning failure-free PRISM programs.

Waleed Alsanie, James Cussens

Int. J. Approx. Reason., 2015

First-order integer programming for MAP problems.

James Cussens

CoRR, 2015

2013

Advances in Bayesian Network Learning using Integer Programming.

James Cussens, Mark Bartlett

Proceedings of the Twenty-Ninth Conference on Uncertainty in Artificial Intelligence, 2013

2012

Online Bayesian inference for the parameters of PRISM programs.

James Cussens

Mach. Learn., 2012

2011

Bayesian network learning with cutting planes.

James Cussens

Proceedings of the UAI 2011, 2011

Probabilistic Instruction Cache Analysis Using Bayesian Networks.

Mark Bartlett, Iain Bate, James Cussens, Dimitar Kazakov

Proceedings of the 17th IEEE International Conference on Embedded and Real-Time Computing Systems and Applications, 2011

Learning a Generative Failure-Free PRISM Clause.

Waleed Alsanie, James Cussens

Proceedings of the Latest Advances in Inductive Logic Programming, 2011

2010

Induction.

James Cussens

Proceedings of the Encyclopedia of Machine Learning, 2010

Approximate Bayesian Computation for the Parameters of PRISM Programs.

James Cussens

Proceedings of the Inductive Logic Programming - 20th International Conference, 2010

Learning Bayesian Networks for Improved Instruction Cache Analysis.

Mark Bartlett, Iain Bate, James Cussens

Proceedings of the Ninth International Conference on Machine Learning and Applications, 2010

Maximum likelihood pedigree reconstruction using integer programming.

James Cussens

Proceedings of the Workshop on Constraint Based Methods for Bioinformatics, 2010

Instruction Cache Prediction Using Bayesian Networks.

Mark Bartlett, Iain Bate, James Cussens

Proceedings of the ECAI 2010, 2010

2009

Discriminative Clustering for Content-Based Tag Recommendation in Social Bookmarking Systems.

Malik Tahir Hassan, Asim Karim, Suresh Manandhar, James Cussens

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.

Silvia Liverani, James Cussens, Jim Q. Smith

Proceedings of the Computational Intelligence Methods for Bioinformatics and Biostatistics, 2009

2008

Bayesian learning of Bayesian networks with informative priors.

Nicos Angelopoulos, James Cussens

Ann. Math. Artif. Intell., 2008

Bayesian network learning by compiling to weighted MAX-SAT.

James Cussens

Proceedings of the UAI 2008, 2008

CLP(<i>BN</i>): Constraint Logic Programming for Probabilistic Knowledge.

Vítor Santos Costa, David Page, James Cussens

Proceedings of the Probabilistic Inductive Logic Programming - Theory and Applications, 2008

2007

Model equivalence of PRISM programs.

James Cussens

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

2006

Inductive Mercury Programming.

Barnaby Fisher, James Cussens

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

2005

Exploiting Informative Priors for Bayesian Classification and Regression Trees.

Nicos Angelopoulos, James Cussens

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.

Nicos Angelopoulos, James Cussens

Proceedings of the Machine Learning, 2005

Exploiting independence for branch operations in Bayesian learning of C&RTs.

Nicos Angelopoulos, James Cussens

Proceedings of the Probabilistic, Logical and Relational Learning - Towards a Synthesis, 30. January, 2005

2004

At the Interface of Inductive Logic Programming and Statistics.

James Cussens

Proceedings of the Inductive Logic Programming, 14th International Conference, 2004

2003

CLP(BN): Constraint Logic Programming for Probabilistic Knowledge.

Vítor Santos Costa, David Page, Maleeha Qazi, James Cussens

Proceedings of the UAI '03, 2003

2002

Issues in Learning Language in Logic.

James Cussens

Proceedings of the Computational Logic: Logic Programming and Beyond, 2002

2001

Parameter Estimation in Stochastic Logic Programs.

James Cussens

Mach. Learn., 2001

Markov Chain Monte Carlo using Tree-Based Priors on Model Structure.

Nicos Angelopoulos, James Cussens

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.

Nicos Angelopoulos, James Cussens

Proceedings of the Web Knowledge Management and Decision Support, 2001

Prolog Issues of an MCMC Algorithm.

Nicos Angelopoulos, James Cussens

Proceedings of the 14th International Conference on Applications of Prolog, 2001

Statistical Aspects of Stochastic Logic Programs.

James Cussens

Proceedings of the Eighth International Workshop on Artificial Intelligence and Statistics, 2001

2000

Stochastic Logic Programs: Sampling, Inference and Applications.

James Cussens

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.

James Cussens, Stephen Pulman

Proceedings of the Fourth Conference on Computational Natural Language Learning, 2000

1999

Integrating Probabilistic and Logical Reasoning.

James Cussens

Electron. Trans. Artif. Intell., 1999

Loglinear models for first-order probabilistic reasoning.

James Cussens

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.

Saso Dzeroski, James Cussens, Suresh Manandhar

Proceedings of the Learning Language in Logic, 1999

Experiments in Inductive Chart Parsing.

James Cussens, Stephen G. Pulman

Proceedings of the Learning Language in Logic, 1999

Morphosyntactic Tagging of Slovene Using Progol.

James Cussens, Saso Dzeroski, Tomaz Erjavec

Proceedings of the Inductive Logic Programming, 9th International Workshop, 1999

1998

Using Prior Probabilities and Density Estimation for Relational Classification.

James Cussens

Proceedings of the Inductive Logic Programming, 8th International Workshop, 1998

1997

Part-of-Speech Tagging Using Progol.

James Cussens

Proceedings of the Inductive Logic Programming, 7th International Workshop, 1997

1996

Deduction, induction and probabilistic support.

James Cussens

Synth., 1996

1995

A Bayesian Analysis of Algorithms for Learning Finite Functions.

James Cussens

Proceedings of the Machine Learning, 1995

1993

Bayes and Pseudo-Bayes Estimates of Conditional Probabilities and Their Reliability.

James Cussens

Proceedings of the Machine Learning: ECML-93, 1993

Generating Explicit Orderings for Non-monotonic Logics.

James Cussens, Anthony Hunter, Ashwin Srinivasan

Proceedings of the 11th National Conference on Artificial Intelligence. Washington, 1993

1992

Using Maximum Entropy in a Defeasible Logic with Probabilistic Semantics.

James Cussens, Anthony Hunter

Proceedings of the IPMU '92, 1992

1991

Using Defeasible Logic for a Window on a Probabilistic Database: Some Preliminary Notes.

James Cussens, Anthony Hunter

Proceedings of the Symbolic and Quantitative Approaches to Reasoning and Uncertainty, 1991