James Cussens - RankMe

91 papers A* 6A 11B 9C 4Journal 33Unranked 22

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	Learning Bayesian Network Classifiers to Minimize Class Variable Parameters. J. Mach. Learn. Res. Shouta Sugahara, Koya Kato, James Cussens, Maomi Ueno
2023	—	`conf`	Branch-Price-and-Cut for Causal Discovery. CLeaR James Cussens
2022	A	`ed.`	Uncertainty in Artificial Intelligence, Proceedings of the Thirty-Eighth Conference on Uncertainty in Artificial Intelligence, UAI 2022, 1-5 August 2022, Eindhoven, The Netherlands. UAI James Cussens, Kun Zhang
2021	J	`jnl`	The dual polyhedron to the chordal graph polytope and the rebuttal of the chordal graph conjecture. Int. J. Approx. Reason. Milan Studený, James Cussens, Václav Kratochvíl
2020	—	`conf`	A Score-and-Search Approach to Learning Bayesian Networks with Noisy-OR Relations. PGM Charupriya Sharma, Zhenyu A. Liao, James Cussens, Peter van Beek
2020	J	`jnl`	A Score-and-Search Approach to Learning Bayesian Networks with Noisy-OR Relations. CoRR Charupriya Sharma, Zhenyu A. Liao, James Cussens, Peter van Beek
2020	—	`conf`	Dual Formulation of the Chordal Graph Conjecture. PGM Milan Studený, James Cussens, Václav Kratochvíl
2020	—	`conf`	GOBNILP: Learning Bayesian network structure with integer programming. PGM James Cussens
2020	—	`conf`	Kernel-based Approach for Learning Causal Graphs from Mixed Data. PGM Teny Handhayani, James Cussens
2020	J	`jnl`	Learning All Credible Bayesian Network Structures for Model Averaging. CoRR Zhenyu A. Liao, Charupriya Sharma, James Cussens, Peter van Beek
2020	A	`conf`	On Pruning for Score-Based Bayesian Network Structure Learning. AISTATS Alvaro Henrique Chaim Correia, James Cussens, Cassio P. de Campos
2019	A*	`conf`	Finding All Bayesian Network Structures within a Factor of Optimal. AAAI Zhenyu A. Liao, Charupriya Sharma, James Cussens, Peter van Beek
2019	J	`jnl`	Kernel-based Approach to Handle Mixed Data for Inferring Causal Graphs. CoRR Teny Handhayani, James Cussens
2019	J	`jnl`	On Pruning for Score-Based Bayesian Network Structure Learning. CoRR Alvaro H. C. Correia, James Cussens, Cassio P. de Campos
2019	C	`conf`	Online Causal Structure Learning in the Presence of Latent Variables. ICMLA Durdane Kocacoban, James Cussens
2019	J	`jnl`	Online Causal Structure Learning in the Presence of Latent Variables. CoRR Durdane Kocacoban, James Cussens
2018	J	`jnl`	Finding All Bayesian Network Structures within a Factor of Optimal. CoRR Zhenyu A. Liao, Charupriya Sharma, James Cussens, Peter van Beek
2018	J	`jnl`	Finding Minimal Cost Herbrand Models with Branch-Cut-and-Price. CoRR James Cussens
2018	—	`conf`	Markov Random Field MAP as Set Partitioning. PGM James Cussens
2018	J	`jnl`	Preface to the special issue on inductive logic programming. Mach. Learn. James Cussens, Alessandra Russo
2018	J	`jnl`	Probabilistic logic programming (PLP) 2016. Int. J. Approx. Reason. Arjen Hommersom, James Cussens
2017	A*	`conf`	Bayesian Network Structure Learning with Integer Programming: Polytopes, Facets and Complexity (Extended Abstract). IJCAI James Cussens, Matti Järvisalo, Janne H. Korhonen, Mark Bartlett
2017	J	`jnl`	Bayesian Network Structure Learning with Integer Programming: Polytopes, Facets and Complexity. J. Artif. Intell. Res. James Cussens, Matti Järvisalo, Janne H. Korhonen, Mark Bartlett
2017	J	`jnl`	Distributional logic programming for Bayesian knowledge representation. Int. J. Approx. Reason. Nicos Angelopoulos, James Cussens
2017	—	`ch.`	Induction. Encyclopedia of Machine Learning and Data Mining James Cussens
2017	B	`ed.`	Inductive Logic Programming - 26th International Conference, ILP 2016, London, UK, September 4-6, 2016, Revised Selected Papers ILP James Cussens, Alessandra Russo
2017	J	`jnl`	Integer Linear Programming for the Bayesian network structure learning problem. Artif. Intell. Mark Bartlett, James Cussens
2017	J	`jnl`	Polyhedral aspects of score equivalence in Bayesian network structure learning. Math. Program. James Cussens, David Haws, Milan Studený
2017	—	`ed.`	Proceedings of the 26th International Conference on Inductive Logic Programming (Short papers), London, UK, 2016. ILP (Short Papers) James Cussens, Alessandra Russo
2017	J	`jnl`	Towards using the chordal graph polytope in learning decomposable models. Int. J. Approx. Reason. Milan Studený, James Cussens
2016	J	`jnl`	Bayesian Network Structure Learning with Integer Programming: Polytopes, Facets, and Complexity. CoRR James Cussens, Matti Järvisalo, Janne H. Korhonen, Mark Bartlett
2016	J	`jnl`	Exact estimation of multiple directed acyclic graphs. Stat. Comput. Chris J. Oates, Jim Q. Smith, Sach Mukherjee, James Cussens
2016	—	`conf`	The Chordal Graph Polytope for Learning Decomposable Models. Probabilistic Graphical Models Milan Studený, James Cussens
2015	J	`jnl`	First-order integer programming for MAP problems. CoRR James Cussens
2015	J	`jnl`	Introduction to the special issue on probability, logic and learning. Theory Pract. Log. Program. James Cussens, Luc De Raedt, Angelika Kimmig, Taisuke Sato
2015	J	`jnl`	Learning failure-free PRISM programs. Int. J. Approx. Reason. Waleed Alsanie, James Cussens
2013	A	`conf`	Advances in Bayesian Network Learning using Integer Programming. UAI James Cussens, Mark Bartlett
2013	J	`jnl`	Advances in Bayesian Network Learning using Integer Programming. CoRR James Cussens, Mark Bartlett
2013	J	`jnl`	Loglinear models for first-order probabilistic reasoning CoRR James Cussens
2013	J	`jnl`	Markov Chain Monte Carlo using Tree-Based Priors on Model Structure CoRR Nicos Angelopoulos, James Cussens
2013	J	`jnl`	Stochastic Logic Programs: Sampling, Inference and Applications CoRR James Cussens
2012	J	`jnl`	Bayesian network learning by compiling to weighted MAX-SAT CoRR James Cussens
2012	J	`jnl`	Bayesian network learning with cutting planes CoRR James Cussens
2012	J	`jnl`	CLP(BN): Constraint Logic Programming for Probabilistic Knowledge CoRR Vítor Santos Costa, David Page, Maleeha Qazi, James Cussens
2012	J	`jnl`	Online Bayesian inference for the parameters of PRISM programs. Mach. Learn. James Cussens
2011	A	`conf`	Bayesian network learning with cutting planes. UAI James Cussens
2011	—	`conf`	Learning a Generative Failure-Free PRISM Clause. ILP (Late Breaking Papers) Waleed Alsanie, James Cussens
2011	B	`conf`	Online Bayesian Inference for the Parameters of PRISM Programs. ILP James Cussens
2011	—	`conf`	Probabilistic Instruction Cache Analysis Using Bayesian Networks. RTCSA (1) Mark Bartlett, Iain Bate, James Cussens, Dimitar Kazakov
2010	B	`conf`	Approximate Bayesian Computation for the Parameters of PRISM Programs. ILP James Cussens
2010	—	`ch.`	Induction. Encyclopedia of Machine Learning James Cussens
2010	A	`conf`	Instruction Cache Prediction Using Bayesian Networks. ECAI Mark Bartlett, Iain Bate, James Cussens
2010	C	`conf`	Learning Bayesian Networks for Improved Instruction Cache Analysis. ICMLA Mark Bartlett, Iain Bate, James Cussens
2010	—	`conf`	Maximum likelihood pedigree reconstruction using integer programming. WCB@ICLP James Cussens
2009	—	`conf`	Discriminative Clustering for Content-Based Tag Recommendation in Social Bookmarking Systems. DC@PKDD/ECML Malik Tahir Hassan, Asim Karim, Suresh Manandhar, James Cussens
2009	—	`conf`	On Generative Parameterisations of Markov Logic Networks. MLG/SRL@ILP James Cussens
2009	—	`conf`	Searching a Multivariate Partition Space Using MAX-SAT. CIBB Silvia Liverani, James Cussens, Jim Q. Smith
2008	J	`jnl`	Bayesian learning of Bayesian networks with informative priors. Ann. Math. Artif. Intell. Nicos Angelopoulos, James Cussens
2008	A	`conf`	Bayesian network learning by compiling to weighted MAX-SAT. UAI James Cussens
2008	—	`ch.`	CLP( Probabilistic Inductive Logic Programming Vítor Santos Costa, David Page, James Cussens
2007	—	`conf`	Model equivalence of PRISM programs. Probabilistic, Logical and Relational Learning - A Further Synthesis James Cussens
2006	B	`conf`	Inductive Mercury Programming. ILP Barnaby Fisher, James Cussens
2005	A*	`conf`	Exploiting Informative Priors for Bayesian Classification and Regression Trees. IJCAI Nicos Angelopoulos, James Cussens
2005	—	`conf`	Exploiting independence for branch operations in Bayesian learning of C&RTs. Probabilistic, Logical and Relational Learning Nicos Angelopoulos, James Cussens
2005	A*	`conf`	Tempering for Bayesian C&RT. ICML Nicos Angelopoulos, James Cussens
2004	B	`conf`	At the Interface of Inductive Logic Programming and Statistics. ILP James Cussens
2003	A	`conf`	CLP(BN): Constraint Logic Programming for Probabilistic Knowledge. UAI Vítor Santos Costa, David Page, Maleeha Qazi, James Cussens
2002	—	`conf`	Issues in Learning Language in Logic. Computational Logic: Logic Programming and Beyond James Cussens
2001	A	`conf`	Markov Chain Monte Carlo using Tree-Based Priors on Model Structure. UAI Nicos Angelopoulos, James Cussens
2001	J	`jnl`	Parameter Estimation in Stochastic Logic Programs. Mach. Learn. James Cussens
2001	—	`conf`	Prolog Issues and Experimental Results of an MCMC Algorithm. INAP (LNCS Volume) Nicos Angelopoulos, James Cussens
2001	—	`conf`	Prolog Issues of an MCMC Algorithm. INAP Nicos Angelopoulos, James Cussens
2001	A	`conf`	Statistical Aspects of Stochastic Logic Programs. AISTATS James Cussens
2000	—	`conf`	Incorporating Linguistics Constraints into Inductive Logic Programming. CoNLL/LLL James Cussens, Stephen Pulman
2000	B	`ed.`	Inductive Logic Programming, 10th International Conference, ILP 2000, London, UK, July 24-27, 2000, Proceedings ILP James Cussens, Alan M. Frisch
2000	—	`ed.`	Inductive Logic Programming, 10th International Conference, ILP 2000, Work-in-progress reports, London, UK, July 2000, Proceedings ILP Work-in-progress reports James Cussens, Alan M. Frisch
2000	—	`ed.`	Learning Language in Logic Learning Language in Logic James Cussens, Saso Dzeroski
2000	A	`conf`	Stochastic Logic Programs: Sampling, Inference and Applications. UAI James Cussens
1999	—	`conf`	An Introduction to Inductive Logic Programming and Learning Language in Logic. Learning Language in Logic Saso Dzeroski, James Cussens, Suresh Manandhar
1999	—	`conf`	Experiments in Inductive Chart Parsing. Learning Language in Logic James Cussens, Stephen G. Pulman
1999	J	`jnl`	Integrating Probabilistic and Logical Reasoning. Electron. Trans. Artif. Intell. James Cussens
1999	A	`conf`	Loglinear models for first-order probabilistic reasoning. UAI James Cussens
1999	B	`conf`	Morphosyntactic Tagging of Slovene Using Progol. ILP James Cussens, Saso Dzeroski, Tomaz Erjavec
1998	B	`conf`	Using Prior Probabilities and Density Estimation for Relational Classification. ILP James Cussens
1997	B	`conf`	Part-of-Speech Tagging Using Progol. ILP James Cussens
1996	J	`jnl`	Deduction, induction and probabilistic support. Synth. James Cussens
1995	A*	`conf`	A Bayesian Analysis of Algorithms for Learning Finite Functions. ICML James Cussens
1993	—	`conf`	Bayes and Pseudo-Bayes Estimates of Conditional Probabilities and Their Reliability. ECML James Cussens
1993	A*	`conf`	Generating Explicit Orderings for Non-monotonic Logics. AAAI James Cussens, Anthony Hunter, Ashwin Srinivasan
1992	C	`conf`	Using Maximum Entropy in a Defeasible Logic with Probabilistic Semantics. IPMU James Cussens, Anthony Hunter
1991	C	`conf`	Using Defeasible Logic for a Window on a Probabilistic Database: Some Preliminary Notes. ECSQARU James Cussens, Anthony Hunter