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Charles Elkan: [Publications] [Author Rank by year] [Co-authors] [Prefers] [Cites] [Cited by]

Publications of Author

  1. Charles Elkan
    Independence of Logic Database Queries and Updates. [Citation Graph (9, 16)][DBLP]
    PODS, 1990, pp:154-160 [Conf]
  2. Charles Elkan
    A Decision Procedure for Conjunctive Query Disjointness. [Citation Graph (4, 11)][DBLP]
    PODS, 1989, pp:134-139 [Conf]
  3. Alvaro E. Monge, Charles Elkan
    An Efficient Domain-Independent Algorithm for Detecting Approximately Duplicate Database Records. [Citation Graph (3, 0)][DBLP]
    DMKD, 1997, pp:0-0 [Conf]
  4. Charles Elkan
    The Paradoxical Success of Fuzzy Logic. [Citation Graph (1, 0)][DBLP]
    AAAI, 1993, pp:698-703 [Conf]
  5. Charles Elkan, David A. McAllester
    Automated Inductive Reasoning about Logic Programs. [Citation Graph (1, 0)][DBLP]
    ICLP/SLP, 1988, pp:876-892 [Conf]
  6. Alvaro E. Monge, Charles Elkan
    The Field Matching Problem: Algorithms and Applications. [Citation Graph (1, 0)][DBLP]
    KDD, 1996, pp:267-270 [Conf]
  7. Charles Elkan
    A Rational Reconstruction of Nonmonotonic Truth Maintenance Systems. [Citation Graph (1, 0)][DBLP]
    Artif. Intell., 1990, v:43, n:2, pp:219-234 [Journal]
  8. Charles Elkan
    Incremental, Approximate Planning. [Citation Graph (0, 0)][DBLP]
    AAAI, 1990, pp:145-150 [Conf]
  9. Charles Elkan
    Reasoning about Unknown, Counterfactual, and Nondeterministic Actions in First-Order Logic. [Citation Graph (0, 0)][DBLP]
    Canadian Conference on AI, 1996, pp:54-68 [Conf]
  10. Karan Bhatia, Charles Elkan
    LPMEME: A Statistical Method for Inductive Logic Programming. [Citation Graph (0, 0)][DBLP]
    Canadian Conference on AI, 1996, pp:227-239 [Conf]
  11. Greg Hamerly, Charles Elkan
    Alternatives to the k-means algorithm that find better clusterings. [Citation Graph (0, 0)][DBLP]
    CIKM, 2002, pp:600-607 [Conf]
  12. David Kauchak, Charles Elkan
    Learning Rules to Improve a Machine Translation System. [Citation Graph (0, 0)][DBLP]
    ECML, 2003, pp:205-216 [Conf]
  13. Charles Elkan
    Using the Triangle Inequality to Accelerate k-Means. [Citation Graph (0, 0)][DBLP]
    ICML, 2003, pp:147-153 [Conf]
  14. Charles Elkan
    Clustering documents with an exponential-family approximation of the Dirichlet compound multinomial distribution. [Citation Graph (0, 0)][DBLP]
    ICML, 2006, pp:289-296 [Conf]
  15. Greg Hamerly, Charles Elkan
    Bayesian approaches to failure prediction for disk drives. [Citation Graph (0, 0)][DBLP]
    ICML, 2001, pp:202-209 [Conf]
  16. Rasmus Elsborg Madsen, David Kauchak, Charles Elkan
    Modeling word burstiness using the Dirichlet distribution. [Citation Graph (0, 0)][DBLP]
    ICML, 2005, pp:545-552 [Conf]
  17. Eric Wiewiora, Garrison W. Cottrell, Charles Elkan
    Principled Methods for Advising Reinforcement Learning Agents. [Citation Graph (0, 0)][DBLP]
    ICML, 2003, pp:792-799 [Conf]
  18. Bianca Zadrozny, Charles Elkan
    Obtaining calibrated probability estimates from decision trees and naive Bayesian classifiers. [Citation Graph (0, 0)][DBLP]
    ICML, 2001, pp:609-616 [Conf]
  19. Timothy L. Bailey, Charles Elkan
    Estimating the Accuracy of Learned Concepts. [Citation Graph (0, 0)][DBLP]
    IJCAI, 1993, pp:895-901 [Conf]
  20. Charles Elkan
    The Foundations of Cost-Sensitive Learning. [Citation Graph (0, 0)][DBLP]
    IJCAI, 2001, pp:973-978 [Conf]
  21. Charles Elkan
    Conspiracy Numbers and Caching for Searching And/Or Trees and Theorem-Proving. [Citation Graph (0, 0)][DBLP]
    IJCAI, 1989, pp:341-348 [Conf]
  22. Russell Greiner, Charles Elkan
    Measuring and Improving the Effectiveness of Representations. [Citation Graph (0, 0)][DBLP]
    IJCAI, 1991, pp:518-524 [Conf]
  23. Timothy L. Bailey, Charles Elkan
    Fitting a Mixture Model By Expectation Maximization To Discover Motifs In Biopolymer. [Citation Graph (0, 0)][DBLP]
    ISMB, 1994, pp:28-36 [Conf]
  24. Timothy L. Bailey, Charles Elkan
    The Value of Prior Knowledge in Discovering Motifs with MEME. [Citation Graph (0, 0)][DBLP]
    ISMB, 1995, pp:21-29 [Conf]
  25. Charles Elkan
    Magical thinking in data mining: lessons from CoIL challenge 2000. [Citation Graph (0, 0)][DBLP]
    KDD, 2001, pp:426-431 [Conf]
  26. Charles Elkan
    Shared challenges in data mining and computational biology (abstract of invited talk). [Citation Graph (0, 0)][DBLP]
    BIOKDD, 2001, pp:44- [Conf]
  27. Andrew T. Smith, Charles Elkan
    A Bayesian network framework for reject inference. [Citation Graph (0, 0)][DBLP]
    KDD, 2004, pp:286-295 [Conf]
  28. Bianca Zadrozny, Charles Elkan
    Learning and making decisions when costs and probabilities are both unknown. [Citation Graph (0, 0)][DBLP]
    KDD, 2001, pp:204-213 [Conf]
  29. Bianca Zadrozny, Charles Elkan
    Transforming classifier scores into accurate multiclass probability estimates. [Citation Graph (0, 0)][DBLP]
    KDD, 2002, pp:694-699 [Conf]
  30. Charles Elkan
    Logical Characterizations of Nonmonotonic TMSs. [Citation Graph (0, 0)][DBLP]
    MFCS, 1989, pp:218-224 [Conf]
  31. Greg Hamerly, Charles Elkan
    Learning the k in k-means. [Citation Graph (0, 0)][DBLP]
    NIPS, 2003, pp:- [Conf]
  32. Charles Elkan
    Deriving TF-IDF as a Fisher Kernel. [Citation Graph (0, 0)][DBLP]
    SPIRE, 2005, pp:295-300 [Conf]
  33. Charles Elkan, Russell Greiner
    D. B. Lenat and R. V. Guha, Building Large Knowledge-Based Systems: Representation and Inference in the Cyc Project. [Citation Graph (0, 0)][DBLP]
    Artif. Intell., 1993, v:61, n:1, pp:41-52 [Journal]
  34. Alberto Maria Segre, Charles Elkan
    A High-Performance Explanation-Based Learning Algorithm. [Citation Graph (0, 0)][DBLP]
    Artif. Intell., 1994, v:69, n:1-2, pp:1-50 [Journal]
  35. Alberto Maria Segre, Geoffrey J. Gordon, Charles Elkan
    Exploratory Analysis of Speedup Learning Data Using Epectation Maximization. [Citation Graph (0, 0)][DBLP]
    Artif. Intell., 1996, v:85, n:1-2, pp:301-319 [Journal]
  36. William Noble Grundy, Timothy L. Bailey, Charles Elkan
    ParaMEME: a parallel implementation and a web interface for a DNA and protein motif discovery tool. [Citation Graph (0, 0)][DBLP]
    Computer Applications in the Biosciences, 1996, v:12, n:4, pp:303-310 [Journal]
  37. William Noble Grundy, Timothy L. Bailey, Charles Elkan, Michael E. Baker
    Meta-MEME: motif-based hidden Markov models of protein families. [Citation Graph (0, 0)][DBLP]
    Computer Applications in the Biosciences, 1997, v:13, n:4, pp:397-406 [Journal]
  38. Charles Elkan
    The Paradoxical Success of Fuzzy Logic. [Citation Graph (0, 0)][DBLP]
    IEEE Expert, 1994, v:9, n:4, pp:3-8 [Journal]
  39. Charles Elkan
    Elkan's Reply: The Paradoxical Controversy over Fuzzy Logic. [Citation Graph (0, 0)][DBLP]
    IEEE Expert, 1994, v:9, n:4, pp:47-49 [Journal]
  40. Charles Elkan
    Paradoxes of fuzzy logic, revisited. [Citation Graph (0, 0)][DBLP]
    Int. J. Approx. Reasoning, 2001, v:26, n:2, pp:153-155 [Journal]
  41. David Kauchak, Joseph Smarr, Charles Elkan
    Sources of Success for Boosted Wrapper Induction. [Citation Graph (0, 0)][DBLP]
    Journal of Machine Learning Research, 2004, v:5, n:, pp:499-527 [Journal]
  42. Timothy L. Bailey, Charles Elkan
    Unsupervised Learning of Multiple Motifs in Biopolymers Using Expectation Maximization. [Citation Graph (0, 0)][DBLP]
    Machine Learning, 1995, v:21, n:1-2, pp:51-80 [Journal]
  43. Alberto Maria Segre, Charles Elkan, Alexander Russell
    A Critical Look at Experimental Evaluations of EBL. [Citation Graph (0, 0)][DBLP]
    Machine Learning, 1991, v:6, n:, pp:183-195 [Journal]
  44. Charles Elkan
    Results of the KDD'99 Classifier Learning. [Citation Graph (0, 0)][DBLP]
    SIGKDD Explorations, 2000, v:1, n:2, pp:63-64 [Journal]
  45. Charles Elkan
    KDD'99 Knowledge Discovery Contest. [Citation Graph (0, 0)][DBLP]
    SIGKDD Explorations, 2000, v:1, n:2, pp:78- [Journal]
  46. Fredrik Farnstrom, James Lewis, Charles Elkan
    Scalability for Clustering Algorithms Revisited. [Citation Graph (0, 0)][DBLP]
    SIGKDD Explorations, 2000, v:2, n:1, pp:51-57 [Journal]
  47. Douglas Turnbull, Charles Elkan
    Fast Recognition of Musical Genres Using RBF Networks. [Citation Graph (0, 0)][DBLP]
    IEEE Trans. Knowl. Data Eng., 2005, v:17, n:4, pp:580-584 [Journal]
  48. Andrew T. Smith, Charles Elkan
    Making generative classifiers robust to selection bias. [Citation Graph (0, 0)][DBLP]
    KDD, 2007, pp:657-666 [Conf]
  49. Sanmay Das, Milton H. Saier Jr., Charles Elkan
    Finding Transport Proteins in a General Protein Database. [Citation Graph (0, 0)][DBLP]
    PKDD, 2007, pp:54-66 [Conf]

  50. Learning to Find Relevant Biological Articles without Negative Training Examples. [Citation Graph (, )][DBLP]

  51. Learning a two-stage SVM/CRF sequence classifier. [Citation Graph (, )][DBLP]

  52. Accounting for burstiness in topic models. [Citation Graph (, )][DBLP]

  53. Learning classifiers from only positive and unlabeled data. [Citation Graph (, )][DBLP]

  54. Learning gene regulatory networks from only positive and unlabeled data. [Citation Graph (, )][DBLP]

  55. Technical perspective - Creativity helps influence prediction precision. [Citation Graph (, )][DBLP]

  56. Dyadic Prediction Using a Latent Feature Log-Linear Model [Citation Graph (, )][DBLP]

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