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Jude W. Shavlik: [Publications] [Author Rank by year] [Co-authors] [Prefers] [Cites] [Cited by]

Publications of Author

  1. Geoffrey G. Towell, Jude W. Shavlik, Michiel O. Noordewier
    Refinement ofApproximate Domain Theories by Knowledge-Based Neural Networks. [Citation Graph (1, 0)][DBLP]
    AAAI, 1990, pp:861-866 [Conf]
  2. Geoffrey G. Towell, Mark Craven, Jude W. Shavlik
    Constructive Induction in Knowledge-Based Neural Networks. [Citation Graph (1, 0)][DBLP]
    ML, 1991, pp:213-217 [Conf]
  3. Jude W. Shavlik
    Combining Symbolic and Neural Learning. [Citation Graph (1, 0)][DBLP]
    Machine Learning, 1994, v:14, n:1, pp:321-331 [Journal]
  4. Jude W. Shavlik, Raymond J. Mooney, Geoffrey G. Towell
    Symbolic and Neural Learning Algorithms: An Experimental Comparison. [Citation Graph (1, 0)][DBLP]
    Machine Learning, 1991, v:6, n:, pp:111-143 [Journal]
  5. Richard Maclin, Jude W. Shavlik
    Using Knowledge-Based Neural Networks to Improve Algorithms: Refining the Chou-Fasman Algorithm for Protein Folding. [Citation Graph (0, 0)][DBLP]
    AAAI, 1992, pp:165-170 [Conf]
  6. Richard Maclin, Jude W. Shavlik
    Incorporating Advice into Agents that Learn from Reinforcements. [Citation Graph (0, 0)][DBLP]
    AAAI, 1994, pp:694-699 [Conf]
  7. Richard Maclin, Jude W. Shavlik, Lisa Torrey, Trevor Walker, Edward W. Wild
    Giving Advice about Preferred Actions to Reinforcement Learners Via Knowledge-Based Kernel Regression. [Citation Graph (0, 0)][DBLP]
    AAAI, 2005, pp:819-824 [Conf]
  8. Richard Maclin, Jude W. Shavlik, Trevor Walker, Lisa Torrey
    A Simple and Effective Method for Incorporating Advice into Kernel Methods. [Citation Graph (0, 0)][DBLP]
    AAAI, 2006, pp:- [Conf]
  9. Jude W. Shavlik, Gerald DeJong
    BAGGER: An EBL System that Extends and Generalizes Explanations. [Citation Graph (0, 0)][DBLP]
    AAAI, 1987, pp:516-520 [Conf]
  10. Geoffrey G. Towell, Jude W. Shavlik
    Using Symbolic Learning to Improve Knowledge-Based Neural Networks. [Citation Graph (0, 0)][DBLP]
    AAAI, 1992, pp:177-182 [Conf]
  11. Glenn Fung, Olvi L. Mangasarian, Jude W. Shavlik
    Knowledge-Based Nonlinear Kernel Classifiers. [Citation Graph (0, 0)][DBLP]
    COLT, 2003, pp:102-113 [Conf]
  12. Michael Molla, Jude W. Shavlik, Thomas Albert, Todd Richmond, Steven Smith
    A Self-Tuning Method for One-Chip SNP Identification. [Citation Graph (0, 0)][DBLP]
    CSB, 2004, pp:69-79 [Conf]
  13. Lisa Torrey, Jude W. Shavlik, Trevor Walker, Richard Maclin
    Skill Acquisition Via Transfer Learning and Advice Taking. [Citation Graph (0, 0)][DBLP]
    ECML, 2006, pp:425-436 [Conf]
  14. Lisa Torrey, Trevor Walker, Jude W. Shavlik, Richard Maclin
    Using Advice to Transfer Knowledge Acquired in One Reinforcement Learning Task to Another. [Citation Graph (0, 0)][DBLP]
    ECML, 2005, pp:412-424 [Conf]
  15. Inês de Castro Dutra, David Page, Vítor Santos Costa, Jude W. Shavlik, Michael Waddell
    Toward Automatic Management of Embarrassingly Parallel Applications. [Citation Graph (0, 0)][DBLP]
    Euro-Par, 2003, pp:509-516 [Conf]
  16. Frank DiMaio, Jude W. Shavlik
    Belief Propagation in Large, Highly Connected Graphs for 3D Part-Based Object Recognition. [Citation Graph (0, 0)][DBLP]
    ICDM, 2006, pp:845-850 [Conf]
  17. Mark Craven, David Page, Jude W. Shavlik, Joseph Bockhorst, Jeremy D. Glasner
    Using Multiple Levels of Learning and Diverse Evidence to Uncover Coordinately Controlled Genes. [Citation Graph (0, 0)][DBLP]
    ICML, 2000, pp:199-206 [Conf]
  18. Mark Craven, Jude W. Shavlik
    Learning Symbolic Rules Using Artificial Neural Networks. [Citation Graph (0, 0)][DBLP]
    ICML, 1993, pp:73-80 [Conf]
  19. Mark Craven, Jude W. Shavlik
    Using Sampling and Queries to Extract Rules from Trained Neural Networks. [Citation Graph (0, 0)][DBLP]
    ICML, 1994, pp:37-45 [Conf]
  20. Tina Eliassi-Rad, Jude W. Shavlik
    A Theory-Refinement Approach to Information Extraction. [Citation Graph (0, 0)][DBLP]
    ICML, 2001, pp:130-137 [Conf]
  21. Douglas H. Fisher, Kathleen B. McKusick, Raymond J. Mooney, Jude W. Shavlik, Geoffrey G. Towell
    Processing Issues in Comparisons of Symbolic and Connectionist Learning Systems. [Citation Graph (0, 0)][DBLP]
    ML, 1989, pp:169-173 [Conf]
  22. Richard Maclin, Jude W. Shavlik
    Enriching Vocabularies by Generalizing Explanation Structures. [Citation Graph (0, 0)][DBLP]
    ML, 1989, pp:444-446 [Conf]
  23. Richard Maclin, Jude W. Shavlik
    Refining Domain Theories Expressed as Finite-State Automata. [Citation Graph (0, 0)][DBLP]
    ML, 1991, pp:524-528 [Conf]
  24. David W. Opitz, Jude W. Shavlik
    Using Genetic Search to Refine Knowledge-based Neural Networks. [Citation Graph (0, 0)][DBLP]
    ICML, 1994, pp:208-216 [Conf]
  25. Jude W. Shavlik
    An Empirical Analysis of EBL Approaches for Learning Plan Schemata. [Citation Graph (0, 0)][DBLP]
    ML, 1989, pp:183-187 [Conf]
  26. Jude W. Shavlik, Geoffrey G. Towell
    Combining Explanation-Based Learning and Artificial Neural Networks. [Citation Graph (0, 0)][DBLP]
    ML, 1989, pp:90-93 [Conf]
  27. Mark Craven, Jude W. Shavlik
    Learning to Represent Codons: A Challenge Problem for Constructive Induction. [Citation Graph (0, 0)][DBLP]
    IJCAI, 1993, pp:1319-1324 [Conf]
  28. Jesse Davis, Elizabeth S. Burnside, Inês de Castro Dutra, David Page, Raghu Ramakrishnan, Vítor Santos Costa, Jude W. Shavlik
    View Learning for Statistical Relational Learning: With an Application to Mammography. [Citation Graph (0, 0)][DBLP]
    IJCAI, 2005, pp:677-683 [Conf]
  29. Richard Maclin, Jude W. Shavlik
    Combining the Predictions of Multiple Classifiers: Using Competitive Learning to Initialize Neural Networks. [Citation Graph (0, 0)][DBLP]
    IJCAI, 1995, pp:524-531 [Conf]
  30. Raymond J. Mooney, Jude W. Shavlik, Geoffrey G. Towell, Alan Gove
    An Experimental Comparison of Symbolic and Connectionist Learning Algorithms. [Citation Graph (0, 0)][DBLP]
    IJCAI, 1989, pp:775-780 [Conf]
  31. David W. Opitz, Jude W. Shavlik
    Heuristically Expanding Knowledge-Based Neural Networks. [Citation Graph (0, 0)][DBLP]
    IJCAI, 1993, pp:1360-1365 [Conf]
  32. Jude W. Shavlik
    Learning about Momentum Conservation. [Citation Graph (0, 0)][DBLP]
    IJCAI, 1985, pp:667-669 [Conf]
  33. Jude W. Shavlik
    Acquiring Recursive Concepts with Explanation-Based Learning. [Citation Graph (0, 0)][DBLP]
    IJCAI, 1989, pp:688-693 [Conf]
  34. Jude W. Shavlik, Gerald DeJong
    An Explanation-based Approach to Generalizing Number. [Citation Graph (0, 0)][DBLP]
    IJCAI, 1987, pp:236-238 [Conf]
  35. Fernanda Araujo Baião, Marta Mattoso, Jude W. Shavlik, Gerson Zaverucha
    Applying Theory Revision to the Design of Distributed Databases. [Citation Graph (0, 0)][DBLP]
    ILP, 2003, pp:57-74 [Conf]
  36. Mark Goadrich, Louis Oliphant, Jude W. Shavlik
    Learning Ensembles of First-Order Clauses for Recall-Precision Curves: A Case Study in Biomedical Information Extraction. [Citation Graph (0, 0)][DBLP]
    ILP, 2004, pp:98-115 [Conf]
  37. Héctor Corrada Bravo, David Page, Raghu Ramakrishnan, Jude W. Shavlik, Vítor Santos Costa
    A Framework for Set-Oriented Computation in Inductive Logic Programming and Its Application in Generalizing Inverse Entailment. [Citation Graph (0, 0)][DBLP]
    ILP, 2005, pp:69-86 [Conf]
  38. Frank DiMaio, Jude W. Shavlik
    Learning an Approximation to Inductive Logic Programming Clause Evaluation. [Citation Graph (0, 0)][DBLP]
    ILP, 2004, pp:80-97 [Conf]
  39. Inês de Castro Dutra, David Page, Vítor Santos Costa, Jude W. Shavlik
    An Empirical Evaluation of Bagging in Inductive Logic Programming. [Citation Graph (0, 0)][DBLP]
    ILP, 2002, pp:48-65 [Conf]
  40. Jude W. Shavlik
    Scaling Up ILP: Experiences with Extracting Relations from Biomedical Text. [Citation Graph (0, 0)][DBLP]
    ILP, 2004, pp:7- [Conf]
  41. Mark Craven, David Page, Jude W. Shavlik, Joseph Bockhorst, Jeremy D. Glasner
    A Probabilistic Learning Approach to Whole-Genome Operon Prediction. [Citation Graph (0, 0)][DBLP]
    ISMB, 2000, pp:116-127 [Conf]
  42. Carolyn F. Allex, Schuyler F. Baldwin, Jude W. Shavlik, Frederick R. Blattner
    Improving the Quality of Automatic DNA Sequence Assembly Using Fluorescent Trace-Data Classifications. [Citation Graph (0, 0)][DBLP]
    ISMB, 1996, pp:3-14 [Conf]
  43. Carolyn F. Allex, Schuyler F. Baldwin, Jude W. Shavlik, Frederick R. Blattner
    Increasing Consensus Accuracy in DNA Fragment Assemblies by Incorporating Fluorescent Trace Representations. [Citation Graph (0, 0)][DBLP]
    ISMB, 1997, pp:3-14 [Conf]
  44. Kevin J. Cherkauer, Jude W. Shavlik
    Protein Structure Prediction: Selecting Salient Features from Large Candidate Pools. [Citation Graph (0, 0)][DBLP]
    ISMB, 1993, pp:74-82 [Conf]
  45. Frank DiMaio, Jude W. Shavlik, George N. Phillips
    A probabilistic approach to protein backbone tracing in electron density maps. [Citation Graph (0, 0)][DBLP]
    ISMB (Supplement of Bioinformatics), 2006, pp:81-89 [Conf]
  46. J. B. Tobler, Michael Molla, Emile F. Nuwaysir, R. D. Green, Jude W. Shavlik
    Evaluating machine learning approaches for aiding probe selection for gene-expression arrays. [Citation Graph (0, 0)][DBLP]
    ISMB, 2002, pp:164-171 [Conf]
  47. Jeremy Goecks, Jude W. Shavlik
    Learning users' interests by unobtrusively observing their normal behavior. [Citation Graph (0, 0)][DBLP]
    Intelligent User Interfaces, 2000, pp:129-132 [Conf]
  48. Jude W. Shavlik, Lawrence Birnbaum, William R. Swartout, Eric Horvitz, Barbara Hayes-Roth
    Bridging Science and Applications (Panel). [Citation Graph (0, 0)][DBLP]
    Intelligent User Interfaces, 1999, pp:45-46 [Conf]
  49. Jude W. Shavlik, Susan Calcari, Tina Eliassi-Rad, Jack Solock
    An Instructable, Adaptive Interface for Discovering and Monitoring Information on the World-Wide Web. [Citation Graph (0, 0)][DBLP]
    Intelligent User Interfaces, 1999, pp:157-160 [Conf]
  50. Michael Molla, Peter Andreae, Jeremy D. Glasner, Frederick R. Blattner, Jude W. Shavlik
    Interpreting Microarray Expression Data Using Text Annotating the Genes. [Citation Graph (0, 0)][DBLP]
    JCIS, 2002, pp:1224-1230 [Conf]
  51. Lisa Torrey, Trevor Walker, Jude W. Shavlik, Richard Maclin
    Knowledge transfer via advice taking. [Citation Graph (0, 0)][DBLP]
    K-CAP, 2005, pp:217-218 [Conf]
  52. Kevin J. Cherkauer, Jude W. Shavlik
    Growing Simpler Decision Trees to Facilitate Knowledge Discovery. [Citation Graph (0, 0)][DBLP]
    KDD, 1996, pp:315-318 [Conf]
  53. Jude W. Shavlik, Mark Shavlik
    Selection, combination, and evaluation of effective software sensors for detecting abnormal computer usage. [Citation Graph (0, 0)][DBLP]
    KDD, 2004, pp:276-285 [Conf]
  54. Kevin J. Cherkauer, Jude W. Shavlik
    Rapid Quality Estimation of Neural Network Input Representations. [Citation Graph (0, 0)][DBLP]
    NIPS, 1995, pp:45-51 [Conf]
  55. Mark Craven, Jude W. Shavlik
    Extracting Tree-Structured Representations of Trained Networks. [Citation Graph (0, 0)][DBLP]
    NIPS, 1995, pp:24-30 [Conf]
  56. Frank DiMaio, Jude W. Shavlik, George N. Phillips
    Pictorial Structures for Molecular Modeling: Interpreting Density Maps. [Citation Graph (0, 0)][DBLP]
    NIPS, 2004, pp:- [Conf]
  57. Glenn Fung, Olvi L. Mangasarian, Jude W. Shavlik
    Knowledge-Based Support Vector Machine Classifiers. [Citation Graph (0, 0)][DBLP]
    NIPS, 2002, pp:521-528 [Conf]
  58. David W. Opitz, Jude W. Shavlik
    Generating Accurate and Diverse Members of a Neural-Network Ensemble. [Citation Graph (0, 0)][DBLP]
    NIPS, 1995, pp:535-541 [Conf]
  59. Michiel O. Noordewier, Geoffrey G. Towell, Jude W. Shavlik
    Training Knowledge-Based Neural Networks to Recognize Genes. [Citation Graph (0, 0)][DBLP]
    NIPS, 1990, pp:530-536 [Conf]
  60. Gary M. Scott, Jude W. Shavlik, W. Harmon Ray
    Refined PID Controllers Using Neural Networks. [Citation Graph (0, 0)][DBLP]
    NIPS, 1991, pp:555-562 [Conf]
  61. Geoffrey G. Towell, Jude W. Shavlik
    Interpretation of Artificial Neural Networks: Mapping Knowledge-Based Neural Networks into Rules. [Citation Graph (0, 0)][DBLP]
    NIPS, 1991, pp:977-984 [Conf]
  62. Bee-Chung Chen, Raghu Ramakrishnan, Jude W. Shavlik, Pradeep Tamma
    Bellwether Analysis: Predicting Global Aggregates from Local Regions. [Citation Graph (0, 0)][DBLP]
    VLDB, 2006, pp:655-666 [Conf]
  63. Jude W. Shavlik, Gerald DeJong
    Learning in Mathematically-Based Domains: Understanding and Generalizing Obstacle Cancellations. [Citation Graph (0, 0)][DBLP]
    Artif. Intell., 1990, v:45, n:1-2, pp:1-45 [Journal]
  64. Geoffrey G. Towell, Jude W. Shavlik
    Knowledge-Based Artificial Neural Networks. [Citation Graph (0, 0)][DBLP]
    Artif. Intell., 1994, v:70, n:1-2, pp:119-165 [Journal]
  65. Yolanda Gil, Mark A. Musen, Jude W. Shavlik
    Report on the First International Conference on Knowledge Capture (K-CAP). [Citation Graph (0, 0)][DBLP]
    AI Magazine, 2002, v:23, n:4, pp:107-108 [Journal]
  66. Michael Molla, Michael Waddell, David Page, Jude W. Shavlik
    Using Machine Learning to Design and Interpret Gene-Expression Microarrays. [Citation Graph (0, 0)][DBLP]
    AI Magazine, 2004, v:25, n:1, pp:23-44 [Journal]
  67. David B. Searls, Jude W. Shavlik, Lawrence Hunter
    The First International Conference on Intelligent Systems for Molecular Biology. [Citation Graph (0, 0)][DBLP]
    AI Magazine, 1994, v:15, n:1, pp:12-13 [Journal]
  68. Carolyn F. Allex, Jude W. Shavlik, Frederick R. Blattner
    Neural network input representations that produce accurate consensus sequences from DNA fragment assemblies. [Citation Graph (0, 0)][DBLP]
    Bioinformatics, 1999, v:15, n:9, pp:723-728 [Journal]
  69. Joseph Bockhorst, Mark Craven, David Page, Jude W. Shavlik, Jeremy D. Glasner
    A Bayesian Network Approach to Operon Prediction. [Citation Graph (0, 0)][DBLP]
    Bioinformatics, 2003, v:19, n:10, pp:1227-1235 [Journal]
  70. David W. Opitz, Jude W. Shavlik
    Actively Searching for an Effective Neural Network Ensemble. [Citation Graph (0, 0)][DBLP]
    Connect. Sci., 1996, v:8, n:3, pp:337-354 [Journal]
  71. David W. Opitz, Jude W. Shavlik
    Connectionist Theory Refinement: Genetically Searching the Space of Network Topologies [Citation Graph (0, 0)][DBLP]
    CoRR, 1997, v:0, n:, pp:- [Journal]
  72. Mark Craven, Jude W. Shavlik
    Machine Learning Approaches to Gene Recognition. [Citation Graph (0, 0)][DBLP]
    IEEE Expert, 1994, v:9, n:2, pp:2-10 [Journal]
  73. Mark Craven, Jude W. Shavlik
    Understanding Time-Series Networks: A Case Study in Rule Extraction. [Citation Graph (0, 0)][DBLP]
    Int. J. Neural Syst., 1997, v:8, n:4, pp:373-384 [Journal]
  74. Michael Molla, Peter Andreae, Jeremy D. Glasner, Frederick R. Blattner, Jude W. Shavlik
    Interpreting microarray expression data using text annotating the genes. [Citation Graph (0, 0)][DBLP]
    Inf. Sci., 2002, v:146, n:1-4, pp:75-88 [Journal]
  75. David W. Opitz, Jude W. Shavlik
    Connectionist Theory Refinement: Genetically Searching the Space of Network Topologies. [Citation Graph (0, 0)][DBLP]
    J. Artif. Intell. Res. (JAIR), 1997, v:6, n:, pp:177-209 [Journal]
  76. Olvi L. Mangasarian, Jude W. Shavlik, Edward W. Wild
    Knowledge-Based Kernel Approximation. [Citation Graph (0, 0)][DBLP]
    Journal of Machine Learning Research, 2004, v:5, n:, pp:1127-1141 [Journal]
  77. David W. Pitz, Jude W. Shavlik
    Dynamically adding symbolically meaningful nodes to knowledge-based neural networks. [Citation Graph (0, 0)][DBLP]
    Knowl.-Based Syst., 1995, v:8, n:6, pp:301-311 [Journal]
  78. Richard Maclin, Jude W. Shavlik
    Using Knowledge-Based Neural Networks to Improve Algorithms: Refining the Chou-Fasman Algorithm for Protein Folding. [Citation Graph (0, 0)][DBLP]
    Machine Learning, 1993, v:11, n:, pp:195-215 [Journal]
  79. Richard Maclin, Jude W. Shavlik
    Creating Advice-Taking Reinforcement Learners. [Citation Graph (0, 0)][DBLP]
    Machine Learning, 1996, v:22, n:1-3, pp:251-281 [Journal]
  80. Geoffrey G. Towell, Jude W. Shavlik
    Extracting Refined Rules from Knowledge-Based Neural Networks. [Citation Graph (0, 0)][DBLP]
    Machine Learning, 1993, v:13, n:, pp:71-101 [Journal]
  81. Jude W. Shavlik
    Acquiring Recursive and Iterative Concepts with Explanation-Based Learning. [Citation Graph (0, 0)][DBLP]
    Machine Learning, 1990, v:5, n:, pp:39-40 [Journal]
  82. Jude W. Shavlik, Lawrence Hunter, David B. Searls
    Introduction. [Citation Graph (0, 0)][DBLP]
    Machine Learning, 1995, v:21, n:1-2, pp:5-9 [Journal]
  83. Mark Goadrich, Louis Oliphant, Jude W. Shavlik
    Gleaner: Creating ensembles of first-order clauses to improve recall-precision curves. [Citation Graph (0, 0)][DBLP]
    Machine Learning, 2006, v:64, n:1-3, pp:231-261 [Journal]
  84. Tina Eliassi-Rad, Jude W. Shavlik
    A System for Building Intelligent Agents that Learn to Retrieve and Extract Information. [Citation Graph (0, 0)][DBLP]
    User Model. User-Adapt. Interact., 2003, v:13, n:1-2, pp:35-88 [Journal]
  85. Richard Maclin, Edward W. Wild, Jude W. Shavlik, Lisa Torrey, Trevor Walker
    Refining Rules Incorporated into Knowledge-Based Support Vector Learners Via Successive Linear Programming. [Citation Graph (0, 0)][DBLP]
    AAAI, 2007, pp:584-589 [Conf]

  86. Information Extraction for Clinical Data Mining: A Mammography Case Study. [Citation Graph (, )][DBLP]


  87. Learning Parameters for Relational Probabilistic Models with Noisy-Or Combining Rule. [Citation Graph (, )][DBLP]


  88. Speeding Up Inference in Markov Logic Networks by Preprocessing to Reduce the Size of the Resulting Grounded Network. [Citation Graph (, )][DBLP]


  89. Policy Transfer via Markov Logic Networks. [Citation Graph (, )][DBLP]


  90. Relational Macros for Transfer in Reinforcement Learning. [Citation Graph (, )][DBLP]


  91. Building Relational World Models for Reinforcement Learning. [Citation Graph (, )][DBLP]


  92. Using Bayesian Networks to Direct Stochastic Search in Inductive Logic Programming. [Citation Graph (, )][DBLP]


  93. Combining Clauses with Various Precisions and Recalls to Produce Accurate Probabilistic Estimates. [Citation Graph (, )][DBLP]


  94. Boosting First-Order Clauses for Large, Skewed Data Sets. [Citation Graph (, )][DBLP]


  95. Exploiting Causal Independence in Markov Logic Networks: Combining Undirected and Directed Models. [Citation Graph (, )][DBLP]


  96. Online Knowledge-Based Support Vector Machines. [Citation Graph (, )][DBLP]


  97. Improved Methods for Template-Matching in Electron-Density Maps Using Spherical Harmonics. [Citation Graph (, )][DBLP]


  98. Creating protein models from electron-density maps using particle-filtering methods. [Citation Graph (, )][DBLP]


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