James Cussens

Search results

• 2019

  Finding All Bayesian Network Structures within a Factor of Optimal

  Liao, Z., Sharma, C., Cussens, J. & van Beek, P., 17 Jul 2019, Proceedings of the AAAI Conference on Artificial Intelligence, 33(01). AAAI Press, p. 7892-7899 8 p. (Proceedings of the AAAI Conference on Artificial Intelligence; vol. 33, no. 1).

  Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

  Open Access

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• 2018

  Markov Random Field MAP as Set Partitioning

  Cussens, J., 2018, Proceedings of Machine Learning Research: PGM 2018. Vol. 72. p. 85-96 12 p.

  Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

  Open Access
• 2016

  The Chordal Graph Polytope for Learning Decomposable Models

  Studeny´, M. & Cussens, J., 2016, Proceedings of the Eighth International Conference on Probabilistic Graphical Models. Antonucci, A., Corani, G. & Polpo de Campos, C. (eds.). Vol. 52. p. 499-510 12 p. (Journal of Machine Learning Research: Workshop and Conference Proceedings).

  Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

  Open Access

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• 2013

  Advances in Bayesian Network Learning using Integer Programming

  Bartlett, M. & Cussens, J., 2013, Proceedings of the 29th Conference on Uncertainty in Artificial Intelligence (UAI 2013). AUAI Press, p. 182-191 10 p.

  Research output: Chapter in Book/Report/Conference proceeding › Conference contribution
• 2012

  An upper bound for BDeu local scores

  Cussens, J., 2012, Proc. ECAI-2012 workshop on algorithmic issues for inference in graphical models (AIGM 2012).

  Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

• Column generation for exact BN learning: Work in progress

  Cussens, J., 2012, Proc. ECAI-2012 workshop on COmbining COnstraint solving with MIning and LEarning (CoCoMile 2012). p. 21-22

  Research output: Chapter in Book/Report/Conference proceeding › Conference contribution
• 2011

  Approximate Bayesian computation for the parameters of PRISM programs

  Cussens, J., 2011, Proceedings of the 20th International Conference on Inductive Logic Programming. Heidelberg: Springer, Vol. 6489. p. 38-46 9 p.

  Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

• Bayesian network learning with cutting planes

  Cussens, J., 2011, Proceedings of the 27th Conference on Uncertainty in Artificial Intelligence (UAI 2011). Cozman, F. & Pfeffer, A. (eds.). Corvallis, Oregon: AUAI Press, p. 153-160 8 p.

  Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

  File

• Probabilistic Instruction Cache Analysis using Bayesian Networks

  Bartlett, M., Bate, I., Cussens, J. & Kazakov, D., 2011, Proceedings of the 17th IEEE International Conference on Embedded and Real-Time Computing Systems and Applications (RTCSA 2011). Vol. 1. p. 233 - 242

  Research output: Chapter in Book/Report/Conference proceeding › Conference contribution
• 2010

  Instruction Cache Prediction Using Bayesian Networks

  Bartlett, M., Bate, I. & Cussens, J., 1 Aug 2010, Proceedings of the 19th European Conference on Artificial Intelligence (ECAI 2010). Lisbon, Portugal: IOS Press, Vol. 215. p. 1099-1100 2 p. (Frontiers in Artificial Intelligence and Applications; vol. 215).

  Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

• Learning Bayesian Networks for Improved Instruction Cache Analysis

  Bartlett, M., Bate, I. & Cussens, J., 2010, 2010 Ninth International Conference on Machine Learning and Applications: Proceedings of the 9th International Conference on Machine Learning and Applications. IEEE, p. 417-423 7 p.

  Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

• Searching a multivariate partition space using weighted MAX-SAT

  Liverani, S., Cussens, J. & Smith, J. Q., 2010, Proceedings of the Sixth International Meeting on Computational Intelligence Methods for Bioinformatics and Biostatistics (CIBB) 2009. Masulli, F., Peterson, L. & Tagliaferri, R. (eds.). Springer, p. 240-253 14 p. (LNBI 6160).

  Research output: Chapter in Book/Report/Conference proceeding › Conference contribution
• 2009

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

  Hassan, M. T., Karim, A., Manandhar, S. & Cussens, J., 1 Sept 2009, ECML PKDD Discovery Challenge 2009 (DC09). Eisterlehner, F., Hotho, A. & Jäschke, R. (eds.). Bled, Slovenia: CEUR Workshop Proceedings, Vol. 497. p. 85-97 13 p.

  Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

• On Generative Parameterisations of Markov Logic Networks

  Cussens, J., 1 Jul 2009, Proc. SRL 09.

  Research output: Chapter in Book/Report/Conference proceeding › Conference contribution
• 2008

  Bayesian network learning by compiling to weighted MAX-SAT

  Cussens, J., 2008, Proceedings of the 24th Conference on Uncertainty in Artificial Intelligence (UAI 2008). McAllester, D. & Myllymaki, P. (eds.). Corvallis, Oregon: AUAI Press, p. 105-112 8 p.

  Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

  File
• 2007

  Inductive mercury programming

  Fisher, B. & Cussens, J., 2007, Inductive Logic Programming. Muggleton, S., Otero, R. & Tamaddoni-Nezhad, A. (eds.). BERLIN: Springer, p. 199-213 15 p.

  Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

• Model Equivalence of PRISM programs

  Cussens, J., 2007, Proceedings of the Dagstuhl seminar: Probabilistic, Logical and Relational Learning - A Further Synthesis.

  Research output: Chapter in Book/Report/Conference proceeding › Conference contribution
• 2005

  Exploiting informative priors for Bayesian classification and regression trees

  Angelopoulos, N., Cussens, J., Pack Kaelbling, L. (ed.) & Saffiotti, A. (ed.), 2005, Proceedings of the Nineteenth International Joint Conference on Artificial Intelligence. Professional Book Center, p. 641-646 5 p.

  Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

• Tempering for Bayesian C&RT

  Cussens, J., Wrobel, S. (ed.), Angelopoulos, N. & De Raedt, L. (ed.), 2005, Proceedings of the 22nd International Conference on Machine Learning. p. 17-24 7 p. (ACM International Conference Proceeding Series; vol. 19).

  Research output: Chapter in Book/Report/Conference proceeding › Conference contribution
• 2004

  At the interface of inductive logic programming and statistics

  Cussens, J., 2004, INDUCTIVE LOGIC PROGRAMMING, PROCEEDINGS. Camacho, R., King, R. & Srinivasan, AS. (eds.). BERLIN: Springer, p. 23 2 p.

  Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

• 2003

  CLP(BN): Constraint Logic Programming for Probabilistic Knowledge

  Santos Costa, V., Page, D., Qazi, M. & Cussens, J., 2003, Proceedings of the Nineteenth Annual Conference on Uncertainty in Artificial Intelligence (UAI--2003). rulff, U. K. & Meek, C. (eds.). Acapulco, Mexico: MORGAN KAUFMANN PUB INC, p. 517-524 8 p.

  Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

• Individuals, relations and structures in probabilistic models

  Cussens, J., 1 Aug 2003, IJCAI Workshop on Learning Statistical Models from Relational Data (SRL2003). Getoor, L. & Jensen, D. (eds.). p. 32-36 5 p.

  Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

• Prolog issues and experimental results of an MCMC algorithm

  Angelopoulos, N. & Cussens, J., 2003, WEB KNOWLEDGE MANAGEMENT AND DECISION SUPPORTS. Bartenstein, O., Geske, U., Hannebauer, M. & Yoshie, O. (eds.). BERLIN: Springer, p. 186-196 11 p.

  Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

• 2001

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

  Angelopoulos, N. & Cussens, J., 1 Aug 2001, Proceedings of the Seventeenth Annual Conference on Uncertainty in Artificial Intelligence (UAI--2001). Breese, J. & Koller, D. (eds.). Seattle: MORGAN KAUFMANN PUB INC, p. 16-23 8 p.

  Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

• Statistical Aspects of Stochastic Logic Programs

  Cussens, J., 1 Jan 2001, Artificial Intelligence and Statistics 2001: Proceedings of the Eighth International Workshop. Jaakkola, T. & Richardson, T. (eds.). Key West, Florida: MORGAN KAUFMANN PUB INC, p. 181-186 6 p.

  Research output: Chapter in Book/Report/Conference proceeding › Conference contribution
• 2000

  Attribute-Value and Relational Learning: A Statistical Viewpoint

  Cussens, J., 2000, Proceedings of the ICML-2000 Workshop on Attribute-Value and Relational Learning: Crossing the Boundaries. De Raedt, L. & Kramer, S. (eds.). p. 35-39 5 p.

  Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

• Incorporating Linguistics Constraints into Inductive Logic Programming

  Cussens, J. & Pulman, S., 1 Sept 2000, Proceedings of CoNLL2000 and LLL2000. Lisbon: Association for Computational Linguistics, p. 184-193 10 p.

  Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

• Stochastic logic programs: Sampling, inference and applications

  Cussens, J., 2000, Proceedings of the Sixteenth Annual Conference on Uncertainty in Artificial Intelligence (UAI--2000). San Francisco, CA: MORGAN KAUFMANN PUB INC, p. 115-122 8 p.

  Research output: Chapter in Book/Report/Conference proceeding › Conference contribution
• 1999

  Loglinear models for first-order probabilistic reasoning

  Cussens, J., 1999, UNCERTAINTY IN ARTIFICIAL INTELLIGENCE, PROCEEDINGS. Laskey, KB. & Prade, H. (eds.). SAN FRANCISCO: MORGAN KAUFMANN PUB INC, p. 126-133 8 p.

  Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

• Morphosyntactic tagging of Slovene using Progol

  Cussens, J., Dzeroski, S. & Erjavec, T., 1999, INDUCTIVE LOGIC PROGRAMMING. Dzeroski, S. & Flach, P. (eds.). BERLIN: Springer, p. 68-79 12 p.

  Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

• 1998

  Using Prior Probabilities and Density Estimation for Relational Classification

  Cussens, J., 1998, Inductive Logic Programming: Proceedings of the 8th International Conference (ILP-98). Page, D. (ed.). Springer, Vol. 1446. p. 106-115 10 p. (Lecture Notes in Artificial Intelligence).

  Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

• 1997

  Part-of-Speech Tagging using Progol

  Cussens, J., 1997, Inductive Logic Programming: Proceedings of the 7th International Workshop (ILP-97). LNAI 1297. Springer, p. 93-108 16 p.

  Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

• Using Inductive Logic Programming for Natural Language Processing

  Cussens, J., Page, D., Muggleton, S. & Srinivasan, A., 1997, ECML'97 -- Workshop Notes on Empirical Learning of Natural Language Tasks. Daelemans, W., Weijters, T. & Bosch, A. V. D. (eds.). Prague: University of Economics, Prague, p. 25-34 10 p.

  Research output: Chapter in Book/Report/Conference proceeding › Conference contribution
• 1995

  A Bayesian Analysis of Algorithms for Learning Finite Functions

  Cussens, J., 1995, Machine Learning: Proceedings of the Twelfth International Conference (ML95). Prieditis, A. & Russell, S. (eds.). San Francisco, CA: Morgan Kaufmann Publishers, p. 142-149 8 p.

  Research output: Chapter in Book/Report/Conference proceeding › Conference contribution
• 1993

  Bayes and pseudo-Bayes estimates of conditional probability and their reliability

  Cussens, J., 1993, Machine Learning: ECML-93. Brazdil, P. B. (ed.). Springer, Vol. 667. p. 136-152 17 p. (LNAI).

  Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

• Generating explicit orderings for non-monotonic logics

  Cussens, J., Hunter, A. & Srinivasan, A., 1993, Proc. of the Eleventh National Conference on Artificial Intelligence (AAAI-93). MIT Press , p. 420-425 6 p.

  Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

• Using maximum entropy in a defeasible logic with probabilistic semantics

  Cussens, J. & Hunter, A., 1993, IPMU'92 - Advanced Techniques in Artificial Intelligence. Bouchon-Meunier, B., Valverde, L. & Yager, R. R. (eds.). Springer, p. 43-52 10 p. (Lecture Notes in Computer Science).

  Research output: Chapter in Book/Report/Conference proceeding › Conference contribution
• 1991

  Using defeasible logic for a window on a probabilistic database: some preliminary notes

  Cussens, J. & Hunter, A., 1991, Symbolic and Quantitative Approaches for Uncertainty. Kruse, R. & Seigel, P. (eds.). Springer, Vol. 548. p. 146-152 7 p.

  Research output: Chapter in Book/Report/Conference proceeding › Conference contribution