James Cussens

Publication Activity (10 Years)

Years Active: 1991-2023
Publications (10 Years): 31

Top Topics

Bayesian Network Structure

Structure Learning

Set Partitioning

Top Venues

Int. J. Approx. Reason.

Publications

James Cussens
Branch-Price-and-Cut for Causal Discovery. CLeaR (2023)
Milan Studený, James Cussens, Václav Kratochvíl
The dual polyhedron to the chordal graph polytope and the rebuttal of the chordal graph conjecture. Int. J. Approx. Reason. 138 (2021)
Charupriya Sharma, Zhenyu A. Liao, James Cussens, Peter van Beek
A Score-and-Search Approach to Learning Bayesian Networks with Noisy-OR Relations. CoRR (2020)
James Cussens
GOBNILP: Learning Bayesian network structure with integer programming. PGM (2020)
Alvaro Henrique Chaim Correia, James Cussens, Cassio P. de Campos
On Pruning for Score-Based Bayesian Network Structure Learning. AISTATS (2020)
Zhenyu A. Liao, Charupriya Sharma, James Cussens, Peter van Beek
Learning All Credible Bayesian Network Structures for Model Averaging. CoRR (2020)
Charupriya Sharma, Zhenyu A. Liao, James Cussens, Peter van Beek
A Score-and-Search Approach to Learning Bayesian Networks with Noisy-OR Relations. PGM (2020)
Teny Handhayani, James Cussens
Kernel-based Approach for Learning Causal Graphs from Mixed Data. PGM (2020)
Milan Studený, James Cussens, Václav Kratochvíl
Dual Formulation of the Chordal Graph Conjecture. PGM (2020)
Alvaro H. C. Correia, James Cussens, Cassio P. de Campos
On Pruning for Score-Based Bayesian Network Structure Learning. CoRR (2019)
Durdane Kocacoban, James Cussens
Online Causal Structure Learning in the Presence of Latent Variables. ICMLA (2019)
Durdane Kocacoban, James Cussens
Online Causal Structure Learning in the Presence of Latent Variables. CoRR (2019)
Teny Handhayani, James Cussens
Kernel-based Approach to Handle Mixed Data for Inferring Causal Graphs. CoRR (2019)
Zhenyu A. Liao, Charupriya Sharma, James Cussens, Peter van Beek
Finding All Bayesian Network Structures within a Factor of Optimal. AAAI (2019)
James Cussens
Markov Random Field MAP as Set Partitioning. PGM (2018)
Zhenyu A. Liao, Charupriya Sharma, James Cussens, Peter van Beek
Finding All Bayesian Network Structures within a Factor of Optimal. CoRR (2018)
Arjen Hommersom, James Cussens
Probabilistic logic programming (PLP) 2016. Int. J. Approx. Reason. 96 (2018)
James Cussens, Alessandra Russo
Preface to the special issue on inductive logic programming. Mach. Learn. 107 (7) (2018)
James Cussens
Finding Minimal Cost Herbrand Models with Branch-Cut-and-Price. CoRR (2018)
James Cussens, Matti Järvisalo, Janne H. Korhonen, Mark Bartlett
Bayesian Network Structure Learning with Integer Programming: Polytopes, Facets and Complexity (Extended Abstract). IJCAI (2017)
Milan Studený, James Cussens
Towards using the chordal graph polytope in learning decomposable models. Int. J. Approx. Reason. 88 (2017)
Nicos Angelopoulos, James Cussens
Distributional logic programming for Bayesian knowledge representation. Int. J. Approx. Reason. 80 (2017)
Mark Bartlett, James Cussens
Integer Linear Programming for the Bayesian network structure learning problem. Artif. Intell. 244 (2017)
James Cussens, Matti Järvisalo, Janne H. Korhonen, Mark Bartlett
Bayesian Network Structure Learning with Integer Programming: Polytopes, Facets and Complexity. J. Artif. Intell. Res. 58 (2017)
James Cussens, David Haws, Milan Studený
Polyhedral aspects of score equivalence in Bayesian network structure learning. Math. Program. 164 (1-2) (2017)
Milan Studený, James Cussens
The Chordal Graph Polytope for Learning Decomposable Models. Probabilistic Graphical Models (2016)
Chris J. Oates, Jim Q. Smith, Sach Mukherjee, James Cussens
Exact estimation of multiple directed acyclic graphs. Stat. Comput. 26 (4) (2016)
James Cussens, Matti Järvisalo, Janne H. Korhonen, Mark Bartlett
Bayesian Network Structure Learning with Integer Programming: Polytopes, Facets, and Complexity. CoRR (2016)
Waleed Alsanie, James Cussens
Learning failure-free PRISM programs. Int. J. Approx. Reason. 67 (2015)
James Cussens, Luc De Raedt, Angelika Kimmig, Taisuke Sato
Introduction to the special issue on probability, logic and learning. Theory Pract. Log. Program. 15 (2) (2015)
James Cussens
First-order integer programming for MAP problems. CoRR (2015)
Nicos Angelopoulos, James Cussens
Markov Chain Monte Carlo using Tree-Based Priors on Model Structure CoRR (2013)
James Cussens, Mark Bartlett
Advances in Bayesian Network Learning using Integer Programming. CoRR (2013)
James Cussens
Loglinear models for first-order probabilistic reasoning CoRR (2013)
James Cussens
Stochastic Logic Programs: Sampling, Inference and Applications CoRR (2013)
James Cussens, Mark Bartlett
Advances in Bayesian Network Learning using Integer Programming. UAI (2013)
James Cussens
Online Bayesian inference for the parameters of PRISM programs. Mach. Learn. 89 (3) (2012)
Vítor Santos Costa, David Page, Maleeha Qazi, James Cussens
CLP(BN): Constraint Logic Programming for Probabilistic Knowledge CoRR (2012)
James Cussens
Bayesian network learning with cutting planes CoRR (2012)
James Cussens
Bayesian network learning by compiling to weighted MAX-SAT CoRR (2012)
James Cussens
Online Bayesian Inference for the Parameters of PRISM Programs. ILP (2011)
Waleed Alsanie, James Cussens
Learning a Generative Failure-Free PRISM Clause. ILP (Late Breaking Papers) (2011)
James Cussens
Bayesian network learning with cutting planes. UAI (2011)
Mark Bartlett, Iain Bate, James Cussens, Dimitar Kazakov
Probabilistic Instruction Cache Analysis Using Bayesian Networks. RTCSA (1) (2011)
Mark Bartlett, Iain Bate, James Cussens
Learning Bayesian Networks for Improved Instruction Cache Analysis. ICMLA (2010)
James Cussens
Maximum likelihood pedigree reconstruction using integer programming. WCB@ICLP (2010)
James Cussens
Approximate Bayesian Computation for the Parameters of PRISM Programs. ILP (2010)
Mark Bartlett, Iain Bate, James Cussens
Instruction Cache Prediction Using Bayesian Networks. ECAI (2010)
Silvia Liverani, James Cussens, Jim Q. Smith
Searching a Multivariate Partition Space Using MAX-SAT. CIBB (2009)
Malik Tahir Hassan, Asim Karim, Suresh Manandhar, James Cussens
Discriminative Clustering for Content-Based Tag Recommendation in Social Bookmarking Systems. DC@PKDD/ECML (2009)
Nicos Angelopoulos, James Cussens
Bayesian learning of Bayesian networks with informative priors. Ann. Math. Artif. Intell. 54 (1-3) (2008)
James Cussens
Bayesian network learning by compiling to weighted MAX-SAT. UAI (2008)
James Cussens
Model equivalence of PRISM programs. Probabilistic, Logical and Relational Learning - A Further Synthesis (2007)
Barnaby Fisher, James Cussens
Inductive Mercury Programming. ILP (2006)
Nicos Angelopoulos, James Cussens
Tempering for Bayesian C&RT. ICML (2005)
Nicos Angelopoulos, James Cussens
Exploiting Informative Priors for Bayesian Classification and Regression Trees. IJCAI (2005)
Nicos Angelopoulos, James Cussens
Exploiting independence for branch operations in Bayesian learning of C&RTs. Probabilistic, Logical and Relational Learning (2005)
James Cussens
At the Interface of Inductive Logic Programming and Statistics. ILP (2004)
Vítor Santos Costa, David Page, Maleeha Qazi, James Cussens
CLP(BN): Constraint Logic Programming for Probabilistic Knowledge. UAI (2003)
James Cussens
Issues in Learning Language in Logic. Computational Logic: Logic Programming and Beyond (2002)
James Cussens
Statistical Aspects of Stochastic Logic Programs. AISTATS (2001)
James Cussens
Parameter Estimation in Stochastic Logic Programs. Mach. Learn. 44 (3) (2001)
Nicos Angelopoulos, James Cussens
Prolog Issues and Experimental Results of an MCMC Algorithm. INAP (LNCS Volume) (2001)
Nicos Angelopoulos, James Cussens
Prolog Issues of an MCMC Algorithm. INAP (2001)
Nicos Angelopoulos, James Cussens
Markov Chain Monte Carlo using Tree-Based Priors on Model Structure. UAI (2001)
James Cussens, Stephen Pulman
Incorporating Linguistics Constraints into Inductive Logic Programming. CoNLL/LLL (2000)
James Cussens
Stochastic Logic Programs: Sampling, Inference and Applications. UAI (2000)
James Cussens, Saso Dzeroski, Tomaz Erjavec
Morphosyntactic Tagging of Slovene Using Progol. ILP (1999)
James Cussens
Loglinear models for first-order probabilistic reasoning. UAI (1999)
James Cussens, Stephen G. Pulman
Experiments in Inductive Chart Parsing. Learning Language in Logic (1999)
Saso Dzeroski, James Cussens, Suresh Manandhar
An Introduction to Inductive Logic Programming and Learning Language in Logic. Learning Language in Logic (1999)
James Cussens
Integrating Probabilistic and Logical Reasoning. Electron. Trans. Artif. Intell. 3 (B) (1999)
James Cussens
Using Prior Probabilities and Density Estimation for Relational Classification. ILP (1998)
James Cussens
Part-of-Speech Tagging Using Progol. ILP (1997)
James Cussens
Deduction, induction and probabilistic support. Synth. 108 (1) (1996)
James Cussens
A Bayesian Analysis of Algorithms for Learning Finite Functions. ICML (1995)
James Cussens
Bayes and Pseudo-Bayes Estimates of Conditional Probabilities and Their Reliability. ECML (1993)
James Cussens, Anthony Hunter, Ashwin Srinivasan
Generating Explicit Orderings for Non-monotonic Logics. AAAI (1993)
James Cussens, Anthony Hunter
Using Maximum Entropy in a Defeasible Logic with Probabilistic Semantics. IPMU (1992)
James Cussens, Anthony Hunter
Using Defeasible Logic for a Window on a Probabilistic Database: Some Preliminary Notes. ECSQARU (1991)