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Jude W. Shavlik Vis

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*2009
99EEJude W. Shavlik, Sriraam Natarajan: Speeding Up Inference in Markov Logic Networks by Preprocessing to Reduce the Size of the Resulting Grounded Network. IJCAI 2009: 1951-1956
98EEFrank DiMaio, Ameet Soni, George N. Phillips, Jude W. Shavlik: Spherical-harmonic decomposition for molecular recognition in electron-density maps. IJDMB 3(2): 205-227 (2009)
97EEBee-Chung Chen, Raghu Ramakrishnan, Jude W. Shavlik, Pradeep Tamma: Bellwether analysis: Searching for cost-effective query-defined predictors in large databases. TKDD 3(1): (2009)
2008
96 Hendrik Blockeel, Jan Ramon, Jude W. Shavlik, Prasad Tadepalli: Inductive Logic Programming, 17th International Conference, ILP 2007, Corvallis, OR, USA, June 19-21, 2007, Revised Selected Papers Springer 2008
95EELisa Torrey, Jude W. Shavlik, Trevor Walker, Richard Maclin: Rule Extraction for Transfer Learning. Rule Extraction from Support Vector Machines 2008: 67-82
94EEHendrik Blockeel, Jude W. Shavlik, Prasad Tadepalli: Guest editors' introduction: special issue on inductive logic programming (ILP-2007). Machine Learning 73(1): 1-2 (2008)
2007
93 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. AAAI 2007: 584-589
92EEFrank DiMaio, Ameet Soni, George N. Phillips, Jude W. Shavlik: Improved Methods for Template-Matching in Electron-Density Maps Using Spherical Harmonics. BIBM 2007: 258-265
91EEMark Goadrich, Jude W. Shavlik: Combining Clauses with Various Precisions and Recalls to Produce Accurate Probabilistic Estimates. ILP 2007: 122-131
90EELouis Oliphant, Jude W. Shavlik: Using Bayesian Networks to Direct Stochastic Search in Inductive Logic Programming. ILP 2007: 191-199
89EELisa Torrey, Jude W. Shavlik, Trevor Walker, Richard Maclin: Relational Macros for Transfer in Reinforcement Learning. ILP 2007: 254-268
88EETrevor Walker, Lisa Torrey, Jude W. Shavlik, Richard Maclin: Building Relational World Models for Reinforcement Learning. ILP 2007: 280-291
87EEFrank DiMaio, Dmitry A. Kondrashov, Eduard Bitto, Ameet Soni, Craig A. Bingman, George N. Phillips Jr., Jude W. Shavlik: Creating protein models from electron-density maps using particle-filtering methods. Bioinformatics 23(21): 2851-2858 (2007)
2006
86 Richard Maclin, Jude W. Shavlik, Trevor Walker, Lisa Torrey: A Simple and Effective Method for Incorporating Advice into Kernel Methods. AAAI 2006
85EELisa Torrey, Jude W. Shavlik, Trevor Walker, Richard Maclin: Skill Acquisition Via Transfer Learning and Advice Taking. ECML 2006: 425-436
84EEFrank DiMaio, Jude W. Shavlik: Belief Propagation in Large, Highly Connected Graphs for 3D Part-Based Object Recognition. ICDM 2006: 845-850
83EEFrank DiMaio, Jude W. Shavlik, George N. Phillips: A probabilistic approach to protein backbone tracing in electron density maps. ISMB (Supplement of Bioinformatics) 2006: 81-89
82EEBee-Chung Chen, Raghu Ramakrishnan, Jude W. Shavlik, Pradeep Tamma: Bellwether Analysis: Predicting Global Aggregates from Local Regions. VLDB 2006: 655-666
81EEMark Goadrich, Louis Oliphant, Jude W. Shavlik: Gleaner: Creating ensembles of first-order clauses to improve recall-precision curves. Machine Learning 64(1-3): 231-261 (2006)
2005
80 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. AAAI 2005: 819-824
79EELisa Torrey, Trevor Walker, Jude W. Shavlik, Richard Maclin: Using Advice to Transfer Knowledge Acquired in One Reinforcement Learning Task to Another. ECML 2005: 412-424
78EEJesse 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. IJCAI 2005: 677-683
77EEHéctor 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. ILP 2005: 69-86
76EELisa Torrey, Trevor Walker, Jude W. Shavlik, Richard Maclin: Knowledge transfer via advice taking. K-CAP 2005: 217-218
2004
75EEMichael Molla, Jude W. Shavlik, Thomas Albert, Todd Richmond, Steven Smith: A Self-Tuning Method for One-Chip SNP Identification. CSB 2004: 69-79
74EEJude W. Shavlik: Scaling Up ILP: Experiences with Extracting Relations from Biomedical Text. ILP 2004: 7
73EEFrank DiMaio, Jude W. Shavlik: Learning an Approximation to Inductive Logic Programming Clause Evaluation. ILP 2004: 80-97
72EEMark Goadrich, Louis Oliphant, Jude W. Shavlik: Learning Ensembles of First-Order Clauses for Recall-Precision Curves: A Case Study in Biomedical Information Extraction. ILP 2004: 98-115
71EEJude W. Shavlik, Mark Shavlik: Selection, combination, and evaluation of effective software sensors for detecting abnormal computer usage. KDD 2004: 276-285
70EEFrank DiMaio, Jude W. Shavlik, George N. Phillips: Pictorial Structures for Molecular Modeling: Interpreting Density Maps. NIPS 2004
69 Michael Molla, Michael Waddell, David Page, Jude W. Shavlik: Using Machine Learning to Design and Interpret Gene-Expression Microarrays. AI Magazine 25(1): 23-44 (2004)
68EEOlvi L. Mangasarian, Jude W. Shavlik, Edward W. Wild: Knowledge-Based Kernel Approximation. Journal of Machine Learning Research 5: 1127-1141 (2004)
2003
67EEGlenn Fung, Olvi L. Mangasarian, Jude W. Shavlik: Knowledge-Based Nonlinear Kernel Classifiers. COLT 2003: 102-113
66EEInês de Castro Dutra, David Page, Vítor Santos Costa, Jude W. Shavlik, Michael Waddell: Toward Automatic Management of Embarrassingly Parallel Applications. Euro-Par 2003: 509-516
65EEFernanda Araujo Baião, Marta Mattoso, Jude W. Shavlik, Gerson Zaverucha: Applying Theory Revision to the Design of Distributed Databases. ILP 2003: 57-74
64 Joseph Bockhorst, Mark Craven, David Page, Jude W. Shavlik, Jeremy D. Glasner: A Bayesian Network Approach to Operon Prediction. Bioinformatics 19(10): 1227-1235 (2003)
63EETina Eliassi-Rad, Jude W. Shavlik: A System for Building Intelligent Agents that Learn to Retrieve and Extract Information. User Model. User-Adapt. Interact. 13(1-2): 35-88 (2003)
2002
62EEInês de Castro Dutra, David Page, Vítor Santos Costa, Jude W. Shavlik: An Empirical Evaluation of Bagging in Inductive Logic Programming. ILP 2002: 48-65
61 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. ISMB 2002: 164-171
60 Michael Molla, Peter Andreae, Jeremy D. Glasner, Frederick R. Blattner, Jude W. Shavlik: Interpreting Microarray Expression Data Using Text Annotating the Genes. JCIS 2002: 1224-1230
59EEGlenn Fung, Olvi L. Mangasarian, Jude W. Shavlik: Knowledge-Based Support Vector Machine Classifiers. NIPS 2002: 521-528
58 Yolanda Gil, Mark A. Musen, Jude W. Shavlik: Report on the First International Conference on Knowledge Capture (K-CAP). AI Magazine 23(4): 107-108 (2002)
57EEMichael Molla, Peter Andreae, Jeremy D. Glasner, Frederick R. Blattner, Jude W. Shavlik: Interpreting microarray expression data using text annotating the genes. Inf. Sci. 146(1-4): 75-88 (2002)
2001
56 Tina Eliassi-Rad, Jude W. Shavlik: A Theory-Refinement Approach to Information Extraction. ICML 2001: 130-137
2000
55 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. ICML 2000: 199-206
54 Mark Craven, David Page, Jude W. Shavlik, Joseph Bockhorst, Jeremy D. Glasner: A Probabilistic Learning Approach to Whole-Genome Operon Prediction. ISMB 2000: 116-127
53EEJeremy Goecks, Jude W. Shavlik: Learning users' interests by unobtrusively observing their normal behavior. IUI 2000: 129-132
1999
52EEJude W. Shavlik, Susan Calcari, Tina Eliassi-Rad, Jack Solock: An Instructable, Adaptive Interface for Discovering and Monitoring Information on the World-Wide Web. IUI 1999: 157-160
51EEJude W. Shavlik, Lawrence Birnbaum, William R. Swartout, Eric Horvitz, Barbara Hayes-Roth: Bridging Science and Applications (Panel). IUI 1999: 45-46
50 Carolyn F. Allex, Jude W. Shavlik, Frederick R. Blattner: Neural network input representations that produce accurate consensus sequences from DNA fragment assemblies. Bioinformatics 15(9): 723-728 (1999)
1998
49 Jude W. Shavlik: Proceedings of the Fifteenth International Conference on Machine Learning (ICML 1998), Madison, Wisconson, USA, July 24-27, 1998 Morgan Kaufmann 1998
1997
48 Carolyn F. Allex, Schuyler F. Baldwin, Jude W. Shavlik, Frederick R. Blattner: Increasing Consensus Accuracy in DNA Fragment Assemblies by Incorporating Fluorescent Trace Representations. ISMB 1997: 3-14
47EEDavid W. Opitz, Jude W. Shavlik: Connectionist Theory Refinement: Genetically Searching the Space of Network Topologies CoRR cs.AI/9705102: (1997)
46EEMark Craven, Jude W. Shavlik: Understanding Time-Series Networks: A Case Study in Rule Extraction. Int. J. Neural Syst. 8(4): 373-384 (1997)
45 David W. Opitz, Jude W. Shavlik: Connectionist Theory Refinement: Genetically Searching the Space of Network Topologies. J. Artif. Intell. Res. (JAIR) 6: 177-209 (1997)
1996
44 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. ISMB 1996: 3-14
43 Kevin J. Cherkauer, Jude W. Shavlik: Growing Simpler Decision Trees to Facilitate Knowledge Discovery. KDD 1996: 315-318
42EEDavid W. Opitz, Jude W. Shavlik: Actively Searching for an Effective Neural Network Ensemble. Connect. Sci. 8(3): 337-354 (1996)
41 Richard Maclin, Jude W. Shavlik: Creating Advice-Taking Reinforcement Learners. Machine Learning 22(1-3): 251-281 (1996)
1995
40 Richard Maclin, Jude W. Shavlik: Combining the Predictions of Multiple Classifiers: Using Competitive Learning to Initialize Neural Networks. IJCAI 1995: 524-531
39EEMark Craven, Jude W. Shavlik: Extracting Tree-Structured Representations of Trained Networks. NIPS 1995: 24-30
38EEKevin J. Cherkauer, Jude W. Shavlik: Rapid Quality Estimation of Neural Network Input Representations. NIPS 1995: 45-51
37EEDavid W. Opitz, Jude W. Shavlik: Generating Accurate and Diverse Members of a Neural-Network Ensemble. NIPS 1995: 535-541
36EEDavid W. Opitz, Jude W. Shavlik: Dynamically adding symbolically meaningful nodes to knowledge-based neural networks. Knowl.-Based Syst. 8(6): 301-311 (1995)
35 Jude W. Shavlik, Lawrence Hunter, David B. Searls: Introduction. Machine Learning 21(1-2): 5-9 (1995)
1994
34 Richard Maclin, Jude W. Shavlik: Incorporating Advice into Agents that Learn from Reinforcements. AAAI 1994: 694-699
33 David W. Opitz, Jude W. Shavlik: Using Genetic Search to Refine Knowledge-based Neural Networks. ICML 1994: 208-216
32 Mark Craven, Jude W. Shavlik: Using Sampling and Queries to Extract Rules from Trained Neural Networks. ICML 1994: 37-45
31 David B. Searls, Jude W. Shavlik, Lawrence Hunter: The First International Conference on Intelligent Systems for Molecular Biology. AI Magazine 15(1): 12-13 (1994)
30 Geoffrey G. Towell, Jude W. Shavlik: Knowledge-Based Artificial Neural Networks. Artif. Intell. 70(1-2): 119-165 (1994)
29EEMark Craven, Jude W. Shavlik: Machine Learning Approaches to Gene Recognition. IEEE Expert 9(2): 2-10 (1994)
28 Jude W. Shavlik: Combining Symbolic and Neural Learning. Machine Learning 14(1): 321-331 (1994)
1993
27 Lawrence Hunter, David B. Searls, Jude W. Shavlik: Proceedings of the 1st International Conference on Intelligent Systems for Molecular Biology, Bethesda, MD, USA, July 1993 AAAI 1993
26 Mark Craven, Jude W. Shavlik: Learning Symbolic Rules Using Artificial Neural Networks. ICML 1993: 73-80
25 Mark Craven, Jude W. Shavlik: Learning to Represent Codons: A Challenge Problem for Constructive Induction. IJCAI 1993: 1319-1324
24 David W. Opitz, Jude W. Shavlik: Heuristically Expanding Knowledge-Based Neural Networks. IJCAI 1993: 1360-1365
23 Kevin J. Cherkauer, Jude W. Shavlik: Protein Structure Prediction: Selecting Salient Features from Large Candidate Pools. ISMB 1993: 74-82
22 Richard Maclin, Jude W. Shavlik: Using Knowledge-Based Neural Networks to Improve Algorithms: Refining the Chou-Fasman Algorithm for Protein Folding. Machine Learning 11: 195-215 (1993)
21 Geoffrey G. Towell, Jude W. Shavlik: Extracting Refined Rules from Knowledge-Based Neural Networks. Machine Learning 13: 71-101 (1993)
1992
20 Richard Maclin, Jude W. Shavlik: Using Knowledge-Based Neural Networks to Improve Algorithms: Refining the Chou-Fasman Algorithm for Protein Folding. AAAI 1992: 165-170
19 Geoffrey G. Towell, Jude W. Shavlik: Using Symbolic Learning to Improve Knowledge-Based Neural Networks. AAAI 1992: 177-182
1991
18 Geoffrey G. Towell, Mark Craven, Jude W. Shavlik: Constructive Induction in Knowledge-Based Neural Networks. ML 1991: 213-217
17 Richard Maclin, Jude W. Shavlik: Refining Domain Theories Expressed as Finite-State Automata. ML 1991: 524-528
16EEGary M. Scott, Jude W. Shavlik, W. Harmon Ray: Refined PID Controllers Using Neural Networks. NIPS 1991: 555-562
15EEGeoffrey G. Towell, Jude W. Shavlik: Interpretation of Artificial Neural Networks: Mapping Knowledge-Based Neural Networks into Rules. NIPS 1991: 977-984
14 Jude W. Shavlik, Raymond J. Mooney, Geoffrey G. Towell: Symbolic and Neural Learning Algorithms: An Experimental Comparison. Machine Learning 6: 111-143 (1991)
1990
13 Geoffrey G. Towell, Jude W. Shavlik, Michiel O. Noordewier: Refinement ofApproximate Domain Theories by Knowledge-Based Neural Networks. AAAI 1990: 861-866
12EEMichiel O. Noordewier, Geoffrey G. Towell, Jude W. Shavlik: Training Knowledge-Based Neural Networks to Recognize Genes. NIPS 1990: 530-536
11 Jude W. Shavlik, Gerald DeJong: Learning in Mathematically-Based Domains: Understanding and Generalizing Obstacle Cancellations. Artif. Intell. 45(1-2): 1-45 (1990)
10 Jude W. Shavlik: Acquiring Recursive and Iterative Concepts with Explanation-Based Learning. Machine Learning 5: 39-40 (1990)
1989
9 Jude W. Shavlik: Acquiring Recursive Concepts with Explanation-Based Learning. IJCAI 1989: 688-693
8 Raymond J. Mooney, Jude W. Shavlik, Geoffrey G. Towell, Alan Gove: An Experimental Comparison of Symbolic and Connectionist Learning Algorithms. IJCAI 1989: 775-780
7 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. ML 1989: 169-173
6 Jude W. Shavlik: An Empirical Analysis of EBL Approaches for Learning Plan Schemata. ML 1989: 183-187
5 Richard Maclin, Jude W. Shavlik: Enriching Vocabularies by Generalizing Explanation Structures. ML 1989: 444-446
4 Jude W. Shavlik, Geoffrey G. Towell: Combining Explanation-Based Learning and Artificial Neural Networks. ML 1989: 90-93
1987
3 Jude W. Shavlik, Gerald DeJong: BAGGER: An EBL System that Extends and Generalizes Explanations. AAAI 1987: 516-520
2 Jude W. Shavlik, Gerald DeJong: An Explanation-based Approach to Generalizing Number. IJCAI 1987: 236-238
1985
1 Jude W. Shavlik: Learning about Momentum Conservation. IJCAI 1985: 667-669

Coauthor Index

1Thomas Albert [75]
2Carolyn F. Allex [44] [48] [50]
3Peter Andreae [57] [60]
4Fernanda Araujo Baião [65]
5Schuyler F. Baldwin [44] [48]
6Craig A. Bingman [87]
7Lawrence Birnbaum (Larry Birnbaum) [51]
8Eduard Bitto [87]
9Frederick R. Blattner [44] [48] [50] [57] [60]
10Hendrik Blockeel [94] [96]
11Joseph Bockhorst [54] [55] [64]
12Héctor Corrada Bravo [77]
13Elizabeth S. Burnside [78]
14Susan Calcari [52]
15Bee-Chung Chen [82] [97]
16Kevin J. Cherkauer [23] [38] [43]
17Vítor Santos Costa [62] [66] [77] [78]
18Mark Craven [18] [25] [26] [29] [32] [39] [46] [54] [55] [64]
19Jesse Davis [78]
20Gerald DeJong [2] [3] [11]
21Frank DiMaio [70] [73] [83] [84] [87] [92] [98]
22Inês de Castro Dutra [62] [66] [78]
23Tina Eliassi-Rad [52] [56] [63]
24Douglas H. Fisher [7]
25Glenn Fung [59] [67]
26Yolanda Gil [58]
27Jeremy D. Glasner [54] [55] [57] [60] [64]
28Mark Goadrich [72] [81] [91]
29Jeremy Goecks [53]
30Alan Gove [8]
31R. D. Green [61]
32Barbara Hayes-Roth [51]
33Eric Horvitz [51]
34Lawrence Hunter [27] [31] [35]
35Dmitry A. Kondrashov [87]
36Richard Maclin [5] [17] [20] [22] [34] [40] [41] [76] [79] [80] [85] [86] [88] [89] [93] [95]
37Olvi L. Mangasarian (O. L. Mangasarian) [59] [67] [68]
38Marta Mattoso (Marta L. Queiros Mattoso) [65]
39Kathleen B. McKusick [7]
40Michael Molla [57] [60] [61] [69] [75]
41Raymond J. Mooney [7] [8] [14]
42Mark A. Musen [58]
43Sriraam Natarajan [99]
44Michiel O. Noordewier [12] [13]
45Emile F. Nuwaysir [61]
46Louis Oliphant [72] [81] [90]
47David W. Opitz [24] [33] [36] [37] [42] [45] [47]
48C. David Page Jr. (David Page) [54] [55] [62] [64] [66] [69] [77] [78]
49George N. Phillips [70] [83] [92] [98]
50George N. Phillips Jr. [87]
51Raghu Ramakrishnan [77] [78] [82] [97]
52Jan Ramon [96]
53W. Harmon Ray [16]
54Todd Richmond [75]
55Gary M. Scott [16]
56David B. Searls [27] [31] [35]
57Mark Shavlik [71]
58Steven Smith [75]
59Jack Solock [52]
60Ameet Soni [87] [92] [98]
61William R. Swartout [51]
62Prasad Tadepalli [94] [96]
63Pradeep Tamma [82] [97]
64J. B. Tobler [61]
65Lisa Torrey [76] [79] [80] [85] [86] [88] [89] [93] [95]
66Geoffrey G. Towell [4] [7] [8] [12] [13] [14] [15] [18] [19] [21] [30]
67Michael Waddell [66] [69]
68Trevor Walker [76] [79] [80] [85] [86] [88] [89] [93] [95]
69Edward W. Wild [68] [80] [93]
70Gerson Zaverucha [65]

Colors in the list of coauthors

Copyright © Tue Nov 3 08:52:44 2009 by Michael Ley (ley@uni-trier.de)