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Linda C. van der Gaag: [Publications] [Author Rank by year] [Co-authors] [Prefers] [Cites] [Cited by]

Publications of Author

  1. Linda C. van der Gaag, Veerle M. H. Coupé
    Sensitive Analysis for Threshold Decision Making with Bayesian Belief Networks. [Citation Graph (0, 0)][DBLP]
    AI*IA, 1999, pp:37-48 [Conf]
  2. Linda C. van der Gaag, Silja Renooij
    On the Evaluation of Probabilistic Networks. [Citation Graph (0, 0)][DBLP]
    AIME, 2001, pp:457-461 [Conf]
  3. Linda C. van der Gaag, Silja Renooij
    Probabilistic Networks as Probabilistic Forecasters. [Citation Graph (0, 0)][DBLP]
    AIME, 2003, pp:294-298 [Conf]
  4. Linda C. van der Gaag, C. L. M. Witteman, Silja Renooij, Michael Egmont-Petersen
    The Effects of Disregarding Test Characteristics in Probabilistic Networks. [Citation Graph (0, 0)][DBLP]
    AIME, 2001, pp:188-198 [Conf]
  5. Wouter P. van Rijsinge, Linda C. van der Gaag, Frank L. J. Visseren, Yolanda van der Graaf
    Compliance with the Hyperlipidaemia Consensus: Clinicians versus the Computer. [Citation Graph (0, 0)][DBLP]
    AIME, 2003, pp:340-344 [Conf]
  6. Danielle Sent, Linda C. van der Gaag
    Detailing Test Characteristics for Probabilistic Networks. [Citation Graph (0, 0)][DBLP]
    AIME, 2003, pp:254-263 [Conf]
  7. Hans L. Bodlaender, Frank van den Eijkhof, Linda C. van der Gaag
    On the Complexity of the MPA Problem in Probabilistic Networks. [Citation Graph (0, 0)][DBLP]
    ECAI, 2002, pp:675-679 [Conf]
  8. Madalina M. Drugan, Linda C. van der Gaag
    A New MDL-Based Function for Feature Selection for Bayesian Network Classifiers. [Citation Graph (0, 0)][DBLP]
    ECAI, 2004, pp:999-1000 [Conf]
  9. Linda C. van der Gaag, Eveline M. Helsper
    Defining Classes of Influences for the Acquisition of Probability Constraints for Bayesian Networks. [Citation Graph (0, 0)][DBLP]
    ECAI, 2004, pp:1101-1102 [Conf]
  10. Eveline M. Helsper, Linda C. van der Gaag
    Building Bayesian Networks through Ontologies. [Citation Graph (0, 0)][DBLP]
    ECAI, 2002, pp:680-684 [Conf]
  11. Silja Renooij, Linda C. van der Gaag, Simon Parsons
    Propagation of Multiple Observations in QPNs Revisited. [Citation Graph (0, 0)][DBLP]
    ECAI, 2002, pp:665-669 [Conf]
  12. Janneke H. Bolt, Linda C. van der Gaag, Silja Renooij
    Introducing Situational Influences in QPNs. [Citation Graph (0, 0)][DBLP]
    ECSQARU, 2003, pp:113-124 [Conf]
  13. Veerle M. H. Coupé, Linda C. van der Gaag
    Supporting Probability Elicitation by Sensitivity Analysis. [Citation Graph (0, 0)][DBLP]
    EKAW, 1997, pp:335-340 [Conf]
  14. Linda C. van der Gaag, Eveline M. Helsper
    Experiences with Modelling Issues in Building Probabilistic Networks. [Citation Graph (0, 0)][DBLP]
    EKAW, 2002, pp:21-26 [Conf]
  15. Eveline M. Helsper, Linda C. van der Gaag, Floris Groenendaal
    Designing a Procedure for the Acquisition of Probability Constraints for Bayesian Networks. [Citation Graph (0, 0)][DBLP]
    EKAW, 2004, pp:280-292 [Conf]
  16. Theodore Charitos, Peter R. de Waal, Linda C. van der Gaag
    Speeding Up Inference in Markovian Models. [Citation Graph (0, 0)][DBLP]
    FLAIRS Conference, 2005, pp:785-790 [Conf]
  17. Silja Renooij, Linda C. van der Gaag
    Decision Making in Qualitative Influence Diagrams. [Citation Graph (0, 0)][DBLP]
    FLAIRS Conference, 1998, pp:410-414 [Conf]
  18. Silja Renooij, Linda C. van der Gaag, Shaw Green, Simon Parsons
    Zooming in on Trade-Offs in Qualitative Probabilistic Networks. [Citation Graph (0, 0)][DBLP]
    FLAIRS Conference, 2000, pp:303-307 [Conf]
  19. Theodore Charitos, Linda C. van der Gaag
    Sensitivity Analysis of Markovian Models. [Citation Graph (0, 0)][DBLP]
    FLAIRS Conference, 2006, pp:806-811 [Conf]
  20. Steven van Dijk, Dirk Thierens, Linda C. van der Gaag
    Building a GA from Design Principles for Learning Bayesian Networks. [Citation Graph (0, 0)][DBLP]
    GECCO, 2003, pp:886-897 [Conf]
  21. Silja Renooij, Simon Parsons, Linda C. van der Gaag
    Context-specific Sign-propagation in Qualitative Probabilistic Networks. [Citation Graph (0, 0)][DBLP]
    IJCAI, 2001, pp:667-672 [Conf]
  22. Petra Geenen, Linda C. van der Gaag, Willie Loeffen, Armin Elbers
    On the Robustness of Feature Selection with Absent and Non-observed Features. [Citation Graph (0, 0)][DBLP]
    ISBMDA, 2004, pp:148-159 [Conf]
  23. Rosa Blanco, Linda C. van der Gaag, Iñaki Inza, Pedro Larrañaga
    Selective Classifiers Can Be Too Restrictive: A Case-Study in Oesophageal Cancer. [Citation Graph (0, 0)][DBLP]
    ISBMDA, 2004, pp:212-223 [Conf]
  24. Eveline M. Helsper, Linda C. van der Gaag, A. J. Feelders, Willie Loeffen, Petra Geenen, Armin Elbers
    Bringing order into bayesian-network construction. [Citation Graph (0, 0)][DBLP]
    K-CAP, 2005, pp:121-128 [Conf]
  25. Steven van Dijk, Linda C. van der Gaag, Dirk Thierens
    A Skeleton-Based Approach to Learning Bayesian Networks from Data. [Citation Graph (0, 0)][DBLP]
    PKDD, 2003, pp:132-143 [Conf]
  26. Niels Peek, Linda C. van der Gaag
    A Case-based Filter for Diagnostic Belief Networks. [Citation Graph (0, 0)][DBLP]
    SCAI, 1995, pp:196-207 [Conf]
  27. Peter Bruza, Linda C. van der Gaag
    Efficient Context-Sensitive Plausible Inference for Information Disclosure. [Citation Graph (0, 0)][DBLP]
    SIGIR, 1993, pp:12-21 [Conf]
  28. Hans L. Bodlaender, Arie M. C. A. Koster, Frank van den Eijkhof, Linda C. van der Gaag
    Pre-processing for Triangulation of Probabilistic Networks. [Citation Graph (0, 0)][DBLP]
    UAI, 2001, pp:32-39 [Conf]
  29. Janneke H. Bolt, Silja Renooij, Linda C. van der Gaag
    Upgrading Ambiguous Signs in QPNs. [Citation Graph (0, 0)][DBLP]
    UAI, 2003, pp:73-80 [Conf]
  30. Marek J. Druzdzel, Linda C. van der Gaag
    Elicitation of Probabilities for Belief Networks: Combining Qualitative and Quantitative Information. [Citation Graph (0, 0)][DBLP]
    UAI, 1995, pp:141-148 [Conf]
  31. Linda C. van der Gaag
    Computing probability intervals under independency constraints. [Citation Graph (0, 0)][DBLP]
    UAI, 1990, pp:457-466 [Conf]
  32. Linda C. van der Gaag, Silja Renooij
    Analysing Sensitivity Data from Probabilistic Networks. [Citation Graph (0, 0)][DBLP]
    UAI, 2001, pp:530-537 [Conf]
  33. Linda C. van der Gaag, Silja Renooij, C. L. M. Witteman, B. M. P. Aleman, B. G. Taal
    How to Elicit Many Probabilities. [Citation Graph (0, 0)][DBLP]
    UAI, 1999, pp:647-654 [Conf]
  34. Uffe Kjærulff, Linda C. van der Gaag
    Making Sensitivity Analysis Computationally Efficient. [Citation Graph (0, 0)][DBLP]
    UAI, 2000, pp:317-325 [Conf]
  35. Silja Renooij, Linda C. van der Gaag
    From Qualitative to Quantitative Probabilistic Networks. [Citation Graph (0, 0)][DBLP]
    UAI, 2002, pp:422-429 [Conf]
  36. Silja Renooij, Linda C. van der Gaag
    Enhancing QPNs for Trade-off Resolution. [Citation Graph (0, 0)][DBLP]
    UAI, 1999, pp:559-566 [Conf]
  37. Silja Renooij, Linda C. van der Gaag, Simon Parsons, Shaw Green
    Pivotal Pruning of Trade-offs in QPNs. [Citation Graph (0, 0)][DBLP]
    UAI, 2000, pp:515-522 [Conf]
  38. Silja Renooij, Linda C. van der Gaag, Simon Parsons
    Context-specific sign-propagation in qualitative probabilistic networks. [Citation Graph (0, 0)][DBLP]
    Artif. Intell., 2002, v:140, n:1/2, pp:207-230 [Journal]
  39. Veerle M. H. Coupé, Linda C. van der Gaag
    Properties of Sensitivity Analysis of Bayesian Belief Networks. [Citation Graph (0, 0)][DBLP]
    Ann. Math. Artif. Intell., 2002, v:36, n:4, pp:323-356 [Journal]
  40. Linda C. van der Gaag, Silja Renooij, C. L. M. Witteman, B. M. P. Aleman, B. G. Taal
    Probabilities for a probabilistic network: a case study in oesophageal cancer. [Citation Graph (0, 0)][DBLP]
    Artificial Intelligence in Medicine, 2002, v:25, n:2, pp:123-148 [Journal]
  41. Peter J. F. Lucas, Linda C. van der Gaag, Ameen Abu-Hanna
    Bayesian networks in biomedicine and health-care. [Citation Graph (0, 0)][DBLP]
    Artificial Intelligence in Medicine, 2004, v:30, n:3, pp:201-214 [Journal]
  42. Danielle Sent, Linda C. van der Gaag
    Generalised reliability characteristics for probabilistic networks. [Citation Graph (0, 0)][DBLP]
    Artificial Intelligence in Medicine, 2005, v:34, n:1, pp:41-52 [Journal]
  43. Gerry Kelleher, Linda C. van der Gaag
    The LazyRMS: Avoiding Work in the ATMS. [Citation Graph (0, 0)][DBLP]
    Computational Intelligence, 1993, v:9, n:, pp:239-253 [Journal]
  44. Linda C. van der Gaag
    Bayesian Belief Networks: Odds and Ends. [Citation Graph (0, 0)][DBLP]
    Comput. J., 1996, v:39, n:2, pp:97-113 [Journal]
  45. Janneke H. Bolt, Linda C. van der Gaag, Silja Renooij
    Introducing situational signs in qualitative probabilistic networks. [Citation Graph (0, 0)][DBLP]
    Int. J. Approx. Reasoning, 2005, v:38, n:3, pp:333-354 [Journal]
  46. A. J. Feelders, Linda C. van der Gaag
    Learning Bayesian network parameters under order constraints. [Citation Graph (0, 0)][DBLP]
    Int. J. Approx. Reasoning, 2006, v:42, n:1-2, pp:37-53 [Journal]
  47. Linda C. van der Gaag
    A conceptual model for inexact reasoning in rule-based systems. [Citation Graph (0, 0)][DBLP]
    Int. J. Approx. Reasoning, 1989, v:3, n:3, pp:239-258 [Journal]
  48. Linda C. van der Gaag
    On evidence absorption for belief networks. [Citation Graph (0, 0)][DBLP]
    Int. J. Approx. Reasoning, 1996, v:15, n:3, pp:265-286 [Journal]
  49. Linda C. van der Gaag
    Different Notions of Uncertainty in Quasi-Probabilistic Models. [Citation Graph (0, 0)][DBLP]
    International Journal of Man-Machine Studies, 1990, v:33, n:5, pp:595-606 [Journal]
  50. Marek J. Druzdzel, Linda C. van der Gaag
    Building Probabilistic Networks: "Where Do the Numbers Come From?" Guest Editors Introduction. [Citation Graph (0, 0)][DBLP]
    IEEE Trans. Knowl. Data Eng., 2000, v:12, n:4, pp:481-486 [Journal]
  51. Danielle Sent, Linda C. van der Gaag
    On the Behaviour of Information Measures for Test Selection. [Citation Graph (0, 0)][DBLP]
    AIME, 2007, pp:316-325 [Conf]
  52. Danielle Sent, Linda C. van der Gaag
    Enhancing Automated Test Selection in Probabilistic Networks. [Citation Graph (0, 0)][DBLP]
    AIME, 2007, pp:331-335 [Conf]
  53. Peter R. de Waal, Linda C. van der Gaag
    Inference and Learning in Multi-dimensional Bayesian Network Classifiers. [Citation Graph (0, 0)][DBLP]
    ECSQARU, 2007, pp:501-511 [Conf]
  54. Silja Renooij, Linda C. van der Gaag
    Evidence-invariant Sensitivity Bounds. [Citation Graph (0, 0)][DBLP]
    UAI, 2004, pp:479-486 [Conf]
  55. Peter R. de Waal, Linda C. van der Gaag
    Stable Independence in Perfect Maps. [Citation Graph (0, 0)][DBLP]
    UAI, 2005, pp:161-168 [Conf]
  56. A. J. Feelders, Linda C. van der Gaag
    Learning Bayesian Network Parameters with Prior Knowledge about Context-Specific Qualitative Influences. [Citation Graph (0, 0)][DBLP]
    UAI, 2005, pp:193-200 [Conf]
  57. Linda C. van der Gaag, Hans L. Bodlaender, A. J. Feelders
    Monotonicity in Bayesian Networks. [Citation Graph (0, 0)][DBLP]
    UAI, 2004, pp:569-576 [Conf]
  58. Peter R. de Waal, Linda C. van der Gaag
    Stable Independance and Complexity of Representation. [Citation Graph (0, 0)][DBLP]
    UAI, 2004, pp:112-119 [Conf]
  59. Silja Renooij, Linda C. van der Gaag
    Exploiting Evidence-dependent Sensitivity Bounds. [Citation Graph (0, 0)][DBLP]
    UAI, 2005, pp:485-492 [Conf]
  60. Theodore Charitos, Linda C. van der Gaag
    Sensitivity Analysis for Threshold Decision Making with Dynamic Networks. [Citation Graph (0, 0)][DBLP]
    UAI, 2006, pp:- [Conf]
  61. Martijn M. Schrage, Arjan van IJzendoorn, Linda C. van der Gaag
    Haskell ready to dazzle the real world. [Citation Graph (0, 0)][DBLP]
    Haskell, 2005, pp:17-26 [Conf]

  62. The Necessity of Bounded Treewidth for Efficient Inference in Bayesian Networks. [Citation Graph (, )][DBLP]


  63. When in Doubt ... Be Indecisive. [Citation Graph (, )][DBLP]


  64. Modelling Patterns of Evidence in Bayesian Networks: A Case-Study in Classical Swine Fever. [Citation Graph (, )][DBLP]


  65. An Empirical Study of the Use of the Noisy-Or Model in a Real-Life Bayesian Network. [Citation Graph (, )][DBLP]


  66. Aligning Bayesian Network Classifiers with Medical Contexts. [Citation Graph (, )][DBLP]


  67. Evidence and Scenario Sensitivities in Naive Bayesian Classifiers. [Citation Graph (, )][DBLP]


  68. Preprocessing the MAP Problem. [Citation Graph (, )][DBLP]


  69. Multi-dimensional Bayesian Network Classifiers. [Citation Graph (, )][DBLP]


  70. Lattices for Studying Monotonicity of Bayesian Networks. [Citation Graph (, )][DBLP]


  71. The Computational Complexity of Sensitivity Analysis and Parameter Tuning. [Citation Graph (, )][DBLP]


  72. Library-style Ontologies to Support Varying Model Views. [Citation Graph (, )][DBLP]


  73. Automated Test Selection in Decision-Support Systems: a Case Study in Oncology. [Citation Graph (, )][DBLP]


  74. Enhanced qualitative probabilistic networks for resolving trade-offs. [Citation Graph (, )][DBLP]


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