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David Heckerman: [Publications] [Author Rank by year] [Co-authors] [Prefers] [Cites] [Cited by]

Publications of Author

  1. David Heckerman
    Bayesian Networks for Data Mining. [Citation Graph (4, 0)][DBLP]
    Data Min. Knowl. Discov., 1997, v:1, n:1, pp:79-119 [Journal]
  2. David Heckerman, Eric Horvitz
    On the Expressiveness of Rule-based Systems for Reasoning with Uncertainty. [Citation Graph (1, 0)][DBLP]
    AAAI, 1987, pp:121-126 [Conf]
  3. Ross D. Shachter, David Heckerman
    Thinking Backward for Knowledge Acquisition. [Citation Graph (1, 0)][DBLP]
    AI Magazine, 1987, v:8, n:3, pp:55-61 [Journal]
  4. David Heckerman, John S. Breese, Koos Rommelse
    Decision-Theoretic Troubleshooting. [Citation Graph (1, 0)][DBLP]
    Commun. ACM, 1995, v:38, n:3, pp:49-57 [Journal]
  5. David Heckerman, Michael P. Wellman
    Bayesian Networks. [Citation Graph (1, 0)][DBLP]
    Commun. ACM, 1995, v:38, n:3, pp:27-30 [Journal]
  6. David Heckerman, Dan Geiger, David Maxwell Chickering
    Learning Bayesian Networks: The Combination of Knowledge and Statistical Data. [Citation Graph (1, 0)][DBLP]
    Machine Learning, 1995, v:20, n:3, pp:197-243 [Journal]
  7. Eric Horvitz, David Heckerman, Curtis Langlotz
    A Framework for Comparing Alternative Formalisms for Plausible Reasoning. [Citation Graph (0, 0)][DBLP]
    AAAI, 1986, pp:210-214 [Conf]
  8. Ronen I. Brafman, David Heckerman, Guy Shani
    Recommendation as a Stochastic Sequential Decision Problem. [Citation Graph (0, 0)][DBLP]
    ICAPS, 2003, pp:164-173 [Conf]
  9. Nebojsa Jojic, Patrice Simard, Brendan J. Frey, David Heckerman
    Separating Appearance from Deformation. [Citation Graph (0, 0)][DBLP]
    ICCV, 2001, pp:288-294 [Conf]
  10. David Heckerman
    Learning With Bayesian Networks (Abstract). [Citation Graph (0, 0)][DBLP]
    ICML, 1995, pp:588- [Conf]
  11. Nir Friedman, Moisés Goldszmidt, David Heckerman, Stuart J. Russell
    Challenge: What is the Impact of Bayesian Networks on Learning? [Citation Graph (0, 0)][DBLP]
    IJCAI (1), 1997, pp:10-15 [Conf]
  12. Eric Horvitz, Gregory F. Cooper, David Heckerman
    Reflection and Action Under Scarce Resources: Theoretical Principles and Empirical Study. [Citation Graph (0, 0)][DBLP]
    IJCAI, 1989, pp:1121-1127 [Conf]
  13. Vladimir Jojic, Nebojsa Jojic, Christopher Meek, Dan Geiger, Adam C. Siepel, David Haussler, David Heckerman
    Efficient approximations for learning phylogenetic HMM models from data. [Citation Graph (0, 0)][DBLP]
    ISMB/ECCB (Supplement of Bioinformatics), 2004, pp:161-168 [Conf]
  14. Nebojsa Jojic, Manuel Reyes-Gomez, David Heckerman, Carl Myers Kadie, Ora Schueler-Furman
    Learning MHC I - peptide binding. [Citation Graph (0, 0)][DBLP]
    ISMB (Supplement of Bioinformatics), 2006, pp:227-235 [Conf]
  15. Igor V. Cadez, David Heckerman, Christopher Meek, Padhraic Smyth, Steven White
    Visualization of navigation patterns on a Web site using model-based clustering. [Citation Graph (0, 0)][DBLP]
    KDD, 2000, pp:280-284 [Conf]
  16. David Heckerman
    Graphical models for data mining. [Citation Graph (0, 0)][DBLP]
    KDD, 2004, pp:2- [Conf]
  17. David Heckerman, Dan Geiger, David Maxwell Chickering
    Learning Bayesian Networks: The Combination of Knowledge and Statistical Data. [Citation Graph (0, 0)][DBLP]
    KDD Workshop, 1994, pp:85-96 [Conf]
  18. Nebojsa Jojic, Vladimir Jojic, Brendan J. Frey, Christopher Meek, David Heckerman
    Using epitomes to model genetic diversity: Rational design of HIV vaccines. [Citation Graph (0, 0)][DBLP]
    NIPS, 2005, pp:- [Conf]
  19. David Heckerman, Carl Myers Kadie, Jennifer Listgarten
    Leveraging Information Across HLA Alleles/Supertypes Improves Epitope Prediction. [Citation Graph (0, 0)][DBLP]
    RECOMB, 2006, pp:296-308 [Conf]
  20. Noah Zaitlen, Manuel Reyes-Gomez, David Heckerman, Nebojsa Jojic
    Shift-Invariant Adaptive Double Threading: Learning MHC II - Peptide Binding. [Citation Graph (0, 0)][DBLP]
    RECOMB, 2007, pp:181-195 [Conf]
  21. Christopher Meek, David Maxwell Chickering, David Heckerman
    Autoregressive Tree Models for Time-Series Analysis. [Citation Graph (0, 0)][DBLP]
    SDM, 2002, pp:- [Conf]
  22. David Maxwell Chickering, David Heckerman
    Targeted advertising with inventory management. [Citation Graph (0, 0)][DBLP]
    ACM Conference on Electronic Commerce, 2000, pp:145-149 [Conf]
  23. John S. Breese, David Heckerman
    Decision-Theoretic Troubleshooting: A Framework for Repair and Experiment. [Citation Graph (0, 0)][DBLP]
    UAI, 1996, pp:124-132 [Conf]
  24. John S. Breese, David Heckerman, Carl Myers Kadie
    Empirical Analysis of Predictive Algorithms for Collaborative Filtering. [Citation Graph (0, 0)][DBLP]
    UAI, 1998, pp:43-52 [Conf]
  25. David Maxwell Chickering, David Heckerman
    A Decision Theoretic Approach to Targeted Advertising. [Citation Graph (0, 0)][DBLP]
    UAI, 2000, pp:82-88 [Conf]
  26. David Maxwell Chickering, David Heckerman
    Efficient Approximations for the Marginal Likelihood of Incomplete Data Given a Bayesian Network. [Citation Graph (0, 0)][DBLP]
    UAI, 1996, pp:158-168 [Conf]
  27. David Maxwell Chickering, David Heckerman
    Fast Learning from Sparse Data. [Citation Graph (0, 0)][DBLP]
    UAI, 1999, pp:109-115 [Conf]
  28. David Maxwell Chickering, David Heckerman, Christopher Meek
    A Bayesian Approach to Learning Bayesian Networks with Local Structure. [Citation Graph (0, 0)][DBLP]
    UAI, 1997, pp:80-89 [Conf]
  29. David Maxwell Chickering, Christopher Meek, David Heckerman
    Large-Sample Learning of Bayesian Networks is NP-Hard. [Citation Graph (0, 0)][DBLP]
    UAI, 2003, pp:124-133 [Conf]
  30. Dan Geiger, David Heckerman
    separable and transitive graphoids. [Citation Graph (0, 0)][DBLP]
    UAI, 1990, pp:65-76 [Conf]
  31. Dan Geiger, David Heckerman
    Advances in Probabilistic Reasoning. [Citation Graph (0, 0)][DBLP]
    UAI, 1991, pp:118-126 [Conf]
  32. Dan Geiger, David Heckerman
    Inference Algorithms for Similarity Networks. [Citation Graph (0, 0)][DBLP]
    UAI, 1993, pp:326-334 [Conf]
  33. Dan Geiger, David Heckerman
    Learning Gaussian Networks. [Citation Graph (0, 0)][DBLP]
    UAI, 1994, pp:235-243 [Conf]
  34. Dan Geiger, David Heckerman
    A Characterization of the Dirichlet Distribution with Application to Learning Bayesian Networks. [Citation Graph (0, 0)][DBLP]
    UAI, 1995, pp:196-207 [Conf]
  35. Dan Geiger, David Heckerman, Christopher Meek
    Asymptotic Model Selection for Directed Networks with Hidden Variables. [Citation Graph (0, 0)][DBLP]
    UAI, 1996, pp:283-290 [Conf]
  36. David Heckerman
    Probabilistic Interpretation for MYCIN's Certainty Factors. [Citation Graph (0, 0)][DBLP]
    UAI, 1985, pp:167-196 [Conf]
  37. David Heckerman
    An axiomatic framework for belief updates. [Citation Graph (0, 0)][DBLP]
    UAI, 1986, pp:11-22 [Conf]
  38. David Heckerman
    An empirical comparison of three inference methods. [Citation Graph (0, 0)][DBLP]
    UAI, 1988, pp:283-302 [Conf]
  39. David Heckerman
    A Tractable Inference Algorithm for Diagnosing Multiple Diseases. [Citation Graph (0, 0)][DBLP]
    UAI, 1989, pp:163-172 [Conf]
  40. David Heckerman
    Similarity networks for the construction of multiple-faults belief networks. [Citation Graph (0, 0)][DBLP]
    UAI, 1990, pp:51-64 [Conf]
  41. David Heckerman
    Causal Independence for Knowledge Acquisition and Inference. [Citation Graph (0, 0)][DBLP]
    UAI, 1993, pp:122-127 [Conf]
  42. David Heckerman
    A Bayesian Approach to Learning Causal Networks. [Citation Graph (0, 0)][DBLP]
    UAI, 1995, pp:285-295 [Conf]
  43. David Heckerman, John S. Breese
    A New Look at Causal Independence. [Citation Graph (0, 0)][DBLP]
    UAI, 1994, pp:286-292 [Conf]
  44. David Heckerman, Dan Geiger, David Maxwell Chickering
    Learning Bayesian Networks: The Combination of Knowledge and Statistical Data. [Citation Graph (0, 0)][DBLP]
    UAI, 1994, pp:293-301 [Conf]
  45. David Heckerman, David Maxwell Chickering, Christopher Meek, Robert Rounthwaite, Carl Myers Kadie
    Dependency Networks for Collaborative Filtering and Data Visualization. [Citation Graph (0, 0)][DBLP]
    UAI, 2000, pp:264-273 [Conf]
  46. David Heckerman, Dan Geiger
    Learning Bayesian Networks: A Unification for Discrete and Gaussian Domains. [Citation Graph (0, 0)][DBLP]
    UAI, 1995, pp:274-284 [Conf]
  47. David Heckerman, Eric Horvitz
    The myth of modularity in rule-based systems for reasoning with uncertainty. [Citation Graph (0, 0)][DBLP]
    UAI, 1986, pp:23-34 [Conf]
  48. David Heckerman, Eric Horvitz
    Problem formulation as the reduction of a decision model. [Citation Graph (0, 0)][DBLP]
    UAI, 1990, pp:159-170 [Conf]
  49. David Heckerman, Eric Horvitz
    Inferring Informational Goals from Free-Text Queries: A Bayesian Approach. [Citation Graph (0, 0)][DBLP]
    UAI, 1998, pp:230-237 [Conf]
  50. David Heckerman, Eric Horvitz, Blackford Middleton
    An Approximate Nonmyopic Computation for Value of Information. [Citation Graph (0, 0)][DBLP]
    UAI, 1991, pp:135-141 [Conf]
  51. David Heckerman, Holly Brügge Jimison
    A Bayesian Perspective on Confidence. [Citation Graph (0, 0)][DBLP]
    UAI, 1987, pp:149-160 [Conf]
  52. David Heckerman, Christopher Meek
    Models and Selection Criteria for Regression and Classification. [Citation Graph (0, 0)][DBLP]
    UAI, 1997, pp:223-228 [Conf]
  53. David Heckerman, Michael Shwe
    Diagnosis of Multiple Faults: A Sensitivity Analysis. [Citation Graph (0, 0)][DBLP]
    UAI, 1993, pp:80-90 [Conf]
  54. David Heckerman, Ross D. Shachter
    A Decision-based View of Causality. [Citation Graph (0, 0)][DBLP]
    UAI, 1994, pp:302-310 [Conf]
  55. David Heckerman, Ross D. Shachter
    A Definition and Graphical Representation for Causality. [Citation Graph (0, 0)][DBLP]
    UAI, 1995, pp:262-273 [Conf]
  56. Eric Horvitz, Jack S. Breese, David Heckerman, David Hovel, Koos Rommelse
    The Lumière Project: Bayesian User Modeling for Inferring the Goals and Needs of Software Users. [Citation Graph (0, 0)][DBLP]
    UAI, 1998, pp:256-265 [Conf]
  57. Eric Horvitz, David Heckerman
    The Inconsistent Use of Measures of Certainty in Artificial Intelligence Research. [Citation Graph (0, 0)][DBLP]
    UAI, 1985, pp:137-152 [Conf]
  58. Carl Myers Kadie, Christopher Meek, David Heckerman
    CFW: A Collaborative Filtering System Using Posteriors over Weights of Evidence. [Citation Graph (0, 0)][DBLP]
    UAI, 2002, pp:242-250 [Conf]
  59. Christopher Meek, David Heckerman
    Structure and Parameter Learning for Causal Independence and Causal Interaction Models. [Citation Graph (0, 0)][DBLP]
    UAI, 1997, pp:366-375 [Conf]
  60. Christopher Meek, Bo Thiesson, David Heckerman
    Staged Mixture Modelling and Boosting. [Citation Graph (0, 0)][DBLP]
    UAI, 2002, pp:335-343 [Conf]
  61. Marina Meila, David Heckerman
    An Experimental Comparison of Several Clustering and Initialization Methods. [Citation Graph (0, 0)][DBLP]
    UAI, 1998, pp:386-395 [Conf]
  62. Ross D. Shachter, David Heckerman
    A backwards view for assessment. [Citation Graph (0, 0)][DBLP]
    UAI, 1986, pp:317-324 [Conf]
  63. Guy Shani, Ronen I. Brafman, David Heckerman
    An MDP-based Recommender System. [Citation Graph (0, 0)][DBLP]
    UAI, 2002, pp:453-460 [Conf]
  64. Henri Jacques Suermondt, Gregory F. Cooper, David Heckerman
    A combination of cutset conditioning with clique-tree propagation in the Pathfinder system. [Citation Graph (0, 0)][DBLP]
    UAI, 1990, pp:245-254 [Conf]
  65. Bo Thiesson, Christopher Meek, David Maxwell Chickering, David Heckerman
    Learning Mixtures of DAG Models. [Citation Graph (0, 0)][DBLP]
    UAI, 1998, pp:504-513 [Conf]
  66. Dan Geiger, David Heckerman
    Knowledge Representation and Inference in Similarity Networks and Bayesian Multinets. [Citation Graph (0, 0)][DBLP]
    Artif. Intell., 1996, v:82, n:1-2, pp:45-74 [Journal]
  67. David Heckerman, Tom Berson, Joshua Goodman, Andrew Ng
    The First Conference on E-mail and Anti-Spam. [Citation Graph (0, 0)][DBLP]
    AI Magazine, 2005, v:26, n:1, pp:96-0 [Journal]
  68. David Heckerman, E. H. Mamdani, Michael P. Wellman
    Real-World Applications of Bayesian Networks - Introduction. [Citation Graph (0, 0)][DBLP]
    Commun. ACM, 1995, v:38, n:3, pp:24-26 [Journal]
  69. Joshua Goodman, Gordon V. Cormack, David Heckerman
    Spam and the ongoing battle for the inbox. [Citation Graph (0, 0)][DBLP]
    Commun. ACM, 2007, v:50, n:2, pp:24-33 [Journal]
  70. Paolo Giudici, David Heckerman, Joe Whittaker
    Statistical Models for Data Mining. [Citation Graph (0, 0)][DBLP]
    Data Min. Knowl. Discov., 2001, v:5, n:3, pp:163-165 [Journal]
  71. Igor V. Cadez, David Heckerman, Christopher Meek, Padhraic Smyth, Steven White
    Model-Based Clustering and Visualization of Navigation Patterns on a Web Site. [Citation Graph (0, 0)][DBLP]
    Data Min. Knowl. Discov., 2003, v:7, n:4, pp:399-424 [Journal]
  72. David Heckerman, Holly Brügge Jimison
    A perspective on confidence and its use in focusing attention during knowledge acquisition. [Citation Graph (0, 0)][DBLP]
    Int. J. Approx. Reasoning, 1988, v:2, n:3, pp:336- [Journal]
  73. David Heckerman, E. H. Mamdani, Michael P. Wellman
    Editorial: real-world applications of uncertain reasoning. [Citation Graph (0, 0)][DBLP]
    Int. J. Hum.-Comput. Stud., 1995, v:42, n:6, pp:573-574 [Journal]
  74. David Maxwell Chickering, Dan Geiger, David Heckerman
    On Finding a Cycle Basis with a Shortest Maximal Cycle. [Citation Graph (0, 0)][DBLP]
    Inf. Process. Lett., 1995, v:54, n:1, pp:55-58 [Journal]
  75. David Heckerman, Ross D. Shachter
    Decision-Theoretic Foundations for Causal Reasoning. [Citation Graph (0, 0)][DBLP]
    J. Artif. Intell. Res. (JAIR), 1995, v:3, n:, pp:405-430 [Journal]
  76. David Heckerman, David Maxwell Chickering, Christopher Meek, Robert Rounthwaite, Carl Myers Kadie
    Dependency Networks for Inference, Collaborative Filtering, and Data Visualization. [Citation Graph (0, 0)][DBLP]
    Journal of Machine Learning Research, 2000, v:1, n:, pp:49-75 [Journal]
  77. David Maxwell Chickering, David Heckerman, Christopher Meek
    Large-Sample Learning of Bayesian Networks is NP-Hard. [Citation Graph (0, 0)][DBLP]
    Journal of Machine Learning Research, 2004, v:5, n:, pp:1287-1330 [Journal]
  78. Christopher Meek, Bo Thiesson, David Heckerman
    The Learning-Curve Sampling Method Applied to Model-Based Clustering. [Citation Graph (0, 0)][DBLP]
    Journal of Machine Learning Research, 2002, v:2, n:, pp:397-418 [Journal]
  79. Guy Shani, David Heckerman, Ronen I. Brafman
    An MDP-Based Recommender System. [Citation Graph (0, 0)][DBLP]
    Journal of Machine Learning Research, 2005, v:6, n:, pp:1265-1295 [Journal]
  80. Francis R. Bach, David Heckerman, Eric Horvitz
    Considering Cost Asymmetry in Learning Classifiers. [Citation Graph (0, 0)][DBLP]
    Journal of Machine Learning Research, 2006, v:7, n:, pp:1713-1741 [Journal]
  81. David Maxwell Chickering, David Heckerman
    Efficient Approximations for the Marginal Likelihood of Bayesian Networks with Hidden Variables. [Citation Graph (0, 0)][DBLP]
    Machine Learning, 1997, v:29, n:2-3, pp:181-212 [Journal]
  82. Marina Meila, David Heckerman
    An Experimental Comparison of Model-Based Clustering Methods. [Citation Graph (0, 0)][DBLP]
    Machine Learning, 2001, v:42, n:1/2, pp:9-29 [Journal]
  83. Bo Thiesson, Christopher Meek, David Heckerman
    Accelerating EM for Large Databases. [Citation Graph (0, 0)][DBLP]
    Machine Learning, 2001, v:45, n:3, pp:279-299 [Journal]
  84. Padhraic Smyth, David Heckerman, Michael I. Jordan
    Probabilistic Independence Networks for Hidden Markov Probability Models. [Citation Graph (0, 0)][DBLP]
    Neural Computation, 1997, v:9, n:2, pp:227-269 [Journal]
  85. David Heckerman, Eric Horvitz, Blackford Middleton
    An Approximate Nonmyopic Computation for Value of Information. [Citation Graph (0, 0)][DBLP]
    IEEE Trans. Pattern Anal. Mach. Intell., 1993, v:15, n:3, pp:292-298 [Journal]
  86. Dan Geiger, David Heckerman
    Probabilistic relevance relations. [Citation Graph (0, 0)][DBLP]
    IEEE Transactions on Systems, Man, and Cybernetics, Part A, 1998, v:28, n:1, pp:17-25 [Journal]
  87. Nebojsa Jojic, Vladimir Jojic, David Heckerman
    Joint Discovery of Haplotype Blocks and Complex Trait Associations from SNP Sequences. [Citation Graph (0, 0)][DBLP]
    UAI, 2004, pp:286-292 [Conf]
  88. Bo Thiesson, David Maxwell Chickering, David Heckerman, Christopher Meek
    ARMA Time-Series Modeling with Graphical Models. [Citation Graph (0, 0)][DBLP]
    UAI, 2004, pp:552-560 [Conf]

  89. Continuous Time Dynamic Topic Models. [Citation Graph (, )][DBLP]


  90. PhyloDet: a scalable visualization tool for mapping multiple traits to large evolutionary trees. [Citation Graph (, )][DBLP]


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