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James Cussens: [Publications] [Author Rank by year] [Co-authors] [Prefers] [Cites] [Cited by]

Publications of Author

  1. James Cussens, Anthony Hunter, Ashwin Srinivasan
    Generating Explicit Orderings for Non-monotonic Logics. [Citation Graph (0, 0)][DBLP]
    AAAI, 1993, pp:420-425 [Conf]
  2. James Cussens
    Issues in Learning Language in Logic. [Citation Graph (0, 0)][DBLP]
    Computational Logic: Logic Programming and Beyond, 2002, pp:491-505 [Conf]
  3. Nicos Angelopoulos, James Cussens
    Exploiting independence for branch operations in Bayesian learning of C&RTs. [Citation Graph (0, 0)][DBLP]
    Probabilistic, Logical and Relational Learning, 2005, pp:- [Conf]
  4. James Cussens
    Bayes and Pseudo-Bayes Estimates of Conditional Probabilities and Their Reliability. [Citation Graph (0, 0)][DBLP]
    ECML, 1993, pp:136-152 [Conf]
  5. James Cussens, Anthony Hunter
    Using Defeasible Logic for a Window on a Probabilistic Database: Some Preliminary Notes. [Citation Graph (0, 0)][DBLP]
    ECSQARU, 1991, pp:146-152 [Conf]
  6. Nicos Angelopoulos, James Cussens
    Tempering for Bayesian C&RT. [Citation Graph (0, 0)][DBLP]
    ICML, 2005, pp:17-24 [Conf]
  7. James Cussens
    A Bayesian Analysis of Algorithms for Learning Finite Functions. [Citation Graph (0, 0)][DBLP]
    ICML, 1995, pp:142-149 [Conf]
  8. Nicos Angelopoulos, James Cussens
    Exploiting Informative Priors for Bayesian Classification and Regression Trees. [Citation Graph (0, 0)][DBLP]
    IJCAI, 2005, pp:641-646 [Conf]
  9. James Cussens
    At the Interface of Inductive Logic Programming and Statistics. [Citation Graph (0, 0)][DBLP]
    ILP, 2004, pp:2-3 [Conf]
  10. James Cussens
    Part-of-Speech Tagging Using Progol. [Citation Graph (0, 0)][DBLP]
    ILP, 1997, pp:93-108 [Conf]
  11. James Cussens
    Using Prior Probabilities and Density Estimation for Relational Classification. [Citation Graph (0, 0)][DBLP]
    ILP, 1998, pp:106-115 [Conf]
  12. James Cussens, Saso Dzeroski, Tomaz Erjavec
    Morphosyntactic Tagging of Slovene Using Progol. [Citation Graph (0, 0)][DBLP]
    ILP, 1999, pp:68-79 [Conf]
  13. Nicos Angelopoulos, James Cussens
    Prolog Issues of an MCMC Algorithm. [Citation Graph (0, 0)][DBLP]
    INAP, 2001, pp:246-253 [Conf]
  14. Nicos Angelopoulos, James Cussens
    Prolog Issues and Experimental Results of an MCMC Algorithm. [Citation Graph (0, 0)][DBLP]
    INAP (LNCS Volume), 2001, pp:186-196 [Conf]
  15. James Cussens, Anthony Hunter
    Using Maximum Entropy in a Defeasible Logic with Probabilistic Semantics. [Citation Graph (0, 0)][DBLP]
    IPMU, 1992, pp:43-52 [Conf]
  16. James Cussens, Stephen G. Pulman
    Experiments in Inductive Chart Parsing. [Citation Graph (0, 0)][DBLP]
    Learning Language in Logic, 1999, pp:143-156 [Conf]
  17. Saso Dzeroski, James Cussens, Suresh Manandhar
    An Introduction to Inductive Logic Programming and Learning Language in Logic. [Citation Graph (0, 0)][DBLP]
    Learning Language in Logic, 1999, pp:3-35 [Conf]
  18. Nicos Angelopoulos, James Cussens
    Markov Chain Monte Carlo using Tree-Based Priors on Model Structure. [Citation Graph (0, 0)][DBLP]
    UAI, 2001, pp:16-23 [Conf]
  19. Vítor Santos Costa, David Page, Maleeha Qazi, James Cussens
    CLP(BN): Constraint Logic Programming for Probabilistic Knowledge. [Citation Graph (0, 0)][DBLP]
    UAI, 2003, pp:517-524 [Conf]
  20. James Cussens
    Stochastic Logic Programs: Sampling, Inference and Applications. [Citation Graph (0, 0)][DBLP]
    UAI, 2000, pp:115-122 [Conf]
  21. James Cussens
    Loglinear models for first-order probabilistic reasoning. [Citation Graph (0, 0)][DBLP]
    UAI, 1999, pp:126-133 [Conf]
  22. Dan Geiger, James Cussens
    Parameter Priors for Directed Acyclic Graphical Models and the Characteriration of Several Probability Distributions. [Citation Graph (0, 0)][DBLP]
    UAI, 1999, pp:216-225 [Conf]
  23. James Cussens
    Integrating Probabilistic and Logical Reasoning. [Citation Graph (0, 0)][DBLP]
    Electron. Trans. Artif. Intell., 1999, v:3, n:B, pp:79-103 [Journal]
  24. James Cussens
    Parameter Estimation in Stochastic Logic Programs. [Citation Graph (0, 0)][DBLP]
    Machine Learning, 2001, v:44, n:3, pp:245-271 [Journal]
  25. Barnaby Fisher, James Cussens
    Inductive Mercury Programming. [Citation Graph (0, 0)][DBLP]
    ILP, 2006, pp:199-213 [Conf]

  26. Model equivalence of PRISM programs. [Citation Graph (, )][DBLP]


  27. Instruction Cache Prediction Using Bayesian Networks. [Citation Graph (, )][DBLP]


  28. CLP(BN): Constraint Logic Programming for Probabilistic Knowledge. [Citation Graph (, )][DBLP]


  29. Bayesian network learning by compiling to weighted MAX-SAT. [Citation Graph (, )][DBLP]


  30. Searching a Multivariate Partition Space Using MAX-SAT. [Citation Graph (, )][DBLP]


  31. Bayesian learning of Bayesian networks with informative priors. [Citation Graph (, )][DBLP]


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