Jude W. Shavlik

	2012
123		Ameet Soni, Jude W. Shavlik: Probabilistic Ensembles for Improved Inference in protein-Structure Determination. J. Bioinformatics and Computational Biology 10(1): (2012)
122		Sriraam Natarajan, Tushar Khot, Kristian Kersting, Bernd Gutmann, Jude W. Shavlik: Gradient-based boosting for statistical relational learning: The relational dependency network case. Machine Learning 86(1): 25-56 (2012)
	2011
121		Tushar Khot, Sriraam Natarajan, Kristian Kersting, Jude W. Shavlik: Learning Markov Logic Networks via Functional Gradient Boosting. ICDM 2011: 320-329
120		Sriraam Natarajan, Saket Joshi, Prasad Tadepalli, Kristian Kersting, Jude W. Shavlik: Imitation Learning in Relational Domains: A Functional-Gradient Boosting Approach. IJCAI 2011: 1414-1420
119		Trevor Walker, Gautam Kunapuli, Noah Larsen, David Page, Jude W. Shavlik: Integrating knowledge capture and supervised learning through a human-computer interface. K-CAP 2011: 89-96
118		Gautam Kunapuli, Richard Maclin, Jude W. Shavlik: Advice Refinement in Knowledge-Based SVMs. NIPS 2011: 1728-1736
117		Feng Niu, Christopher Ré, AnHai Doan, Jude W. Shavlik: Tuffy: Scaling up Statistical Inference in Markov Logic Networks using an RDBMS CoRR abs/1104.3216: (2011)
116		Feng Niu, Ce Zhang, Christopher Ré, Jude W. Shavlik: Felix: Scaling Inference for Markov Logic with an Operator-based Approach CoRR abs/1108.0294: (2011)
115		Feng Niu, Christopher Ré, AnHai Doan, Jude W. Shavlik: Tuffy: Scaling up Statistical Inference in Markov Logic Networks using an RDBMS. PVLDB 4(6): 373-384 (2011)
114		Faisal Farooq, Balaji Krishnapuram, Rómer Rosales, Shipeng Yu, Jude W. Shavlik, Raju Kucherlapati: Predictive Models in Personalized Medicine: Neural Information Processing Systems (NIPS), 2010 workshop report. SIGHIT Record 1(1): 23-25 (2011)
	2010
113		Ameet Soni, Craig A. Bingman, Jude W. Shavlik: Guiding belief propagation using domain knowledge for protein-structure determination. BCB 2010: 285-294
112		Gautam Kunapuli, Kristin P. Bennett, Amina Shabbeer, Richard Maclin, Jude W. Shavlik: Online Knowledge-Based Support Vector Machines. ECML/PKDD (2) 2010: 145-161
111		Sriraam Natarajan, Tushar Khot, Daniel Lowd, Prasad Tadepalli, Kristian Kersting, Jude W. Shavlik: Exploiting Causal Independence in Markov Logic Networks: Combining Undirected and Directed Models. ECML/PKDD (2) 2010: 434-450
110		Sriraam Natarajan, Gautam Kunapuli, Kshitij Judah, Prasad Tadepalli, Kristian Kersting, Jude W. Shavlik: Multi-Agent Inverse Reinforcement Learning. ICMLA 2010: 395-400
109		Houssam Nassif, David Page, Mehmet Ayvaci, Jude W. Shavlik, Elizabeth S. Burnside: Uncovering age-specific invasive and DCIS breast cancer rules using inductive logic programming. IHI 2010: 76-82
108		Trevor Walker, Ciaran O'Reilly, Gautam Kunapuli, Sriraam Natarajan, Richard Maclin, David Page, Jude W. Shavlik: Automating the ILP Setup Task: Converting User Advice about Specific Examples into General Background Knowledge. ILP 2010: 253-268
107		Sriraam Natarajan, Tushar Khot, Daniel Lowd, Prasad Tadepalli, Kristian Kersting, Jude W. Shavlik: Exploiting Causal Independence in Markov Logic Networks: Combining Undirected and Directed Models. Statistical Relational Artificial Intelligence 2010
106		Lisa Torrey, Jude W. Shavlik, Trevor Walker, Richard Maclin: Transfer Learning via Advice Taking. Advances in Machine Learning I 2010: 147-170
105		Ryan W. Woods, Louis Oliphant, Kazuhiko Shinki, David Page, Jude W. Shavlik, Elizabeth S. Burnside: Validation of Results from Knowledge Discovery: Mass Density as a Predictor of Breast Cancer. J. Digital Imaging 23(5): 554-561 (2010)
	2009
104		Houssam Nassif, Ryan W. Woods, Elizabeth S. Burnside, Mehmet Ayvaci, Jude W. Shavlik, David Page: Information Extraction for Clinical Data Mining: A Mammography Case Study. ICDM Workshops 2009: 37-42
103		Sriraam Natarajan, Prasad Tadepalli, Gautam Kunapuli, Jude W. Shavlik: Learning Parameters for Relational Probabilistic Models with Noisy-Or Combining Rule. ICMLA 2009: 141-146
102		Jude 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
101		Louis Oliphant, Elizabeth S. Burnside, Jude W. Shavlik: Boosting First-Order Clauses for Large, Skewed Data Sets. ILP 2009: 166-177
100		Lisa Torrey, Jude W. Shavlik: Policy Transfer via Markov Logic Networks. ILP 2009: 234-248
99		Frank 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)
98		Bee-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
97		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
96		Lisa Torrey, Jude W. Shavlik, Trevor Walker, Richard Maclin: Rule Extraction for Transfer Learning. Rule Extraction from Support Vector Machines 2008: 67-82
95		Hendrik 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
94		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
93		Frank 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
92		Mark Goadrich, Jude W. Shavlik: Combining Clauses with Various Precisions and Recalls to Produce Accurate Probabilistic Estimates. ILP 2007: 122-131
91		Louis Oliphant, Jude W. Shavlik: Using Bayesian Networks to Direct Stochastic Search in Inductive Logic Programming. ILP 2007: 191-199
90		Lisa Torrey, Jude W. Shavlik, Trevor Walker, Richard Maclin: Relational Macros for Transfer in Reinforcement Learning. ILP 2007: 254-268
89		Trevor Walker, Lisa Torrey, Jude W. Shavlik, Richard Maclin: Building Relational World Models for Reinforcement Learning. ILP 2007: 280-291
88		Frank 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
87		Richard Maclin, Jude W. Shavlik, Trevor Walker, Lisa Torrey: A Simple and Effective Method for Incorporating Advice into Kernel Methods. AAAI 2006: 427-432
86		Lisa Torrey, Jude W. Shavlik, Trevor Walker, Richard Maclin: Skill Acquisition Via Transfer Learning and Advice Taking. ECML 2006: 425-436
85		Frank DiMaio, Jude W. Shavlik: Belief Propagation in Large, Highly Connected Graphs for 3D Part-Based Object Recognition. ICDM 2006: 845-850
84		Frank 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
83		Bee-Chung Chen, Raghu Ramakrishnan, Jude W. Shavlik, Pradeep Tamma: Bellwether Analysis: Predicting Global Aggregates from Local Regions. VLDB 2006: 655-666
82		Mark 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
81		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
80		Lisa 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
79		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. IJCAI 2005: 677-683
78		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. ILP 2005: 69-86
77		Lisa Torrey, Trevor Walker, Jude W. Shavlik, Richard Maclin: Knowledge transfer via advice taking. K-CAP 2005: 217-218
	2004
76		Michael Molla, Jude W. Shavlik, Thomas Albert, Todd Richmond, Steven Smith: A Self-Tuning Method for One-Chip SNP Identification. CSB 2004: 69-79
75		Jude W. Shavlik: Scaling Up ILP: Experiences with Extracting Relations from Biomedical Text. ILP 2004: 7
74		Frank DiMaio, Jude W. Shavlik: Learning an Approximation to Inductive Logic Programming Clause Evaluation. ILP 2004: 80-97
73		Mark 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
72		Jude W. Shavlik, Mark Shavlik: Selection, combination, and evaluation of effective software sensors for detecting abnormal computer usage. KDD 2004: 276-285
71		Frank DiMaio, Jude W. Shavlik, George N. Phillips: Pictorial Structures for Molecular Modeling: Interpreting Density Maps. NIPS 2004
70		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)
69		Olvi L. Mangasarian, Jude W. Shavlik, Edward W. Wild: Knowledge-Based Kernel Approximation. Journal of Machine Learning Research 5: 1127-1141 (2004)
	2003
68		Glenn Fung, Olvi L. Mangasarian, Jude W. Shavlik: Knowledge-Based Nonlinear Kernel Classifiers. COLT 2003: 102-113
67		Inês 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
66		Fernanda Araujo Baião, Marta Mattoso, Jude W. Shavlik, Gerson Zaverucha: Applying Theory Revision to the Design of Distributed Databases. ILP 2003: 57-74
65		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)
64		Tina 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
63		Inês de Castro Dutra, David Page, Vítor Santos Costa, Jude W. Shavlik: An Empirical Evaluation of Bagging in Inductive Logic Programming. ILP 2002: 48-65
62		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
61		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
60		Glenn Fung, Olvi L. Mangasarian, Jude W. Shavlik: Knowledge-Based Support Vector Machine Classifiers. NIPS 2002: 521-528
59		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)
58		Michael 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
57		Tina Eliassi-Rad, Jude W. Shavlik: A Theory-Refinement Approach to Information Extraction. ICML 2001: 130-137
	2000
56		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
55		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
54		Jeremy Goecks, Jude W. Shavlik: Learning users' interests by unobtrusively observing their normal behavior. IUI 2000: 129-132
	1999
53		Jude 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
52		Jude W. Shavlik, Lawrence Birnbaum, William R. Swartout, Eric Horvitz, Barbara Hayes-Roth: Bridging Science and Applications (Panel). IUI 1999: 45-46
51		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
50		Jude W. Shavlik: Proceedings of the Fifteenth International Conference on Machine Learning (ICML 1998), Madison, Wisconsin, USA, July 24-27, 1998 Morgan Kaufmann 1998
	1997
49		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
48		David W. Opitz, Jude W. Shavlik: Connectionist Theory Refinement: Genetically Searching the Space of Network Topologies CoRR cs.AI/9705102: (1997)
47		Mark Craven, Jude W. Shavlik: Understanding Time-Series Networks: A Case Study in Rule Extraction. Int. J. Neural Syst. 8(4): 373-384 (1997)
46		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
45		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
44		Kevin J. Cherkauer, Jude W. Shavlik: Growing Simpler Decision Trees to Facilitate Knowledge Discovery. KDD 1996: 315-318
43		David W. Opitz, Jude W. Shavlik: Actively Searching for an Effective Neural Network Ensemble. Connect. Sci. 8(3): 337-354 (1996)
42		Richard Maclin, Jude W. Shavlik: Creating Advice-Taking Reinforcement Learners. Machine Learning 22(1-3): 251-281 (1996)
	1995
41		Richard Maclin, Jude W. Shavlik: Combining the Predictions of Multiple Classifiers: Using Competitive Learning to Initialize Neural Networks. IJCAI 1995: 524-531
40		Mark Craven, Jude W. Shavlik: Extracting Tree-Structured Representations of Trained Networks. NIPS 1995: 24-30
39		Kevin J. Cherkauer, Jude W. Shavlik: Rapid Quality Estimation of Neural Network Input Representations. NIPS 1995: 45-51
38		David W. Opitz, Jude W. Shavlik: Generating Accurate and Diverse Members of a Neural-Network Ensemble. NIPS 1995: 535-541
37		David W. Opitz, Jude W. Shavlik: Dynamically adding symbolically meaningful nodes to knowledge-based neural networks. Knowl.-Based Syst. 8(6): 301-311 (1995)
36		Jude W. Shavlik, Lawrence Hunter, David B. Searls: Introduction. Machine Learning 21(1-2): 5-9 (1995)
	1994
35		Richard Maclin, Jude W. Shavlik: Incorporating Advice into Agents that Learn from Reinforcements. AAAI 1994: 694-699
34		David W. Opitz, Jude W. Shavlik: Using Genetic Search to Refine Knowledge-based Neural Networks. ICML 1994: 208-216
33		Mark Craven, Jude W. Shavlik: Using Sampling and Queries to Extract Rules from Trained Neural Networks. ICML 1994: 37-45
32		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)
31		Geoffrey G. Towell, Jude W. Shavlik: Knowledge-Based Artificial Neural Networks. Artif. Intell. 70(1-2): 119-165 (1994)
30		Mark Craven, Jude W. Shavlik: Machine Learning Approaches to Gene Recognition. IEEE Expert 9(2): 2-10 (1994)
29		Jude W. Shavlik: Combining Symbolic and Neural Learning. Machine Learning 14(1): 321-331 (1994)
	1993
28		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
27		Mark Craven, Jude W. Shavlik: Learning Symbolic Rules Using Artificial Neural Networks. ICML 1993: 73-80
26		Mark Craven, Jude W. Shavlik: Learning to Represent Codons: A Challenge Problem for Constructive Induction. IJCAI 1993: 1319-1324
25		David W. Opitz, Jude W. Shavlik: Heuristically Expanding Knowledge-Based Neural Networks. IJCAI 1993: 1360-1365
24		Kevin J. Cherkauer, Jude W. Shavlik: Protein Structure Prediction: Selecting Salient Features from Large Candidate Pools. ISMB 1993: 74-82
23		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)
22		Geoffrey G. Towell, Jude W. Shavlik: Extracting Refined Rules from Knowledge-Based Neural Networks. Machine Learning 13: 71-101 (1993)
	1992
21		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
20		Geoffrey G. Towell, Jude W. Shavlik: Using Symbolic Learning to Improve Knowledge-Based Neural Networks. AAAI 1992: 177-182
19		Gary M. Scott, Jude W. Shavlik, W. Harmon Ray: Refining PID Controllers Using Neural Networks. Neural Computation 4(5): 746-757 (1992)
	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
16		Gary M. Scott, Jude W. Shavlik, W. Harmon Ray: Refined PID Controllers Using Neural Networks. NIPS 1991: 555-562
15		Geoffrey 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
12		Michiel 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

1	Thomas Albert	[76]
2	Carolyn F. Allex	[45] [49] [51]
3	Peter Andreae	[58] [61]
4	Mehmet Ayvaci	[104] [109]
5	Fernanda Araujo Baião	[66]
6	Schuyler F. Baldwin	[45] [49]
7	Kristin P. Bennett	[112]
8	Craig A. Bingman	[88] [113]
9	Lawrence Birnbaum (Larry Birnbaum)	[52]
10	Eduard Bitto	[88]
11	Frederick R. Blattner	[45] [49] [51] [58] [61]
12	Hendrik Blockeel	[95] [97]
13	Joseph Bockhorst	[55] [56] [65]
14	Héctor Corrada Bravo	[78]
15	Elizabeth S. Burnside	[79] [101] [104] [105] [109]
16	Susan Calcari	[53]
17	Bee-Chung Chen	[83] [98]
18	Kevin J. Cherkauer	[24] [39] [44]
19	Vítor Santos Costa	[63] [67] [78] [79]
20	Mark Craven	[18] [26] [27] [30] [33] [40] [47] [55] [56] [65]
21	Jesse Davis	[79]
22	Gerald DeJong	[2] [3] [11]
23	Frank DiMaio	[71] [74] [84] [85] [88] [93] [99]
24	AnHai Doan	[115] [117]
25	Inês de Castro Dutra	[63] [67] [79]
26	Tina Eliassi-Rad	[53] [57] [64]
27	Faisal Farooq	[114]
28	Douglas H. Fisher	[7]
29	Glenn Fung	[60] [68]
30	Yolanda Gil	[59]
31	Jeremy D. Glasner	[55] [56] [58] [61] [65]
32	Mark Goadrich	[73] [82] [92]
33	Jeremy Goecks	[54]
34	Alan Gove	[8]
35	R. D. Green	[62]
36	Bernd Gutmann	[122]
37	Barbara Hayes-Roth	[52]
38	Eric Horvitz	[52]
39	Lawrence Hunter	[28] [32] [36]
40	Saket Joshi	[120]
41	Kshitij Judah	[110]
42	Kristian Kersting	[107] [110] [111] [120] [121] [122]
43	Tushar Khot	[107] [111] [121] [122]
44	Dmitry A. Kondrashov	[88]
45	Balaji Krishnapuram	[114]
46	Raju Kucherlapati	[114]
47	Gautam Kunapuli	[103] [108] [110] [112] [118] [119]
48	Noah Larsen	[119]
49	Daniel Lowd	[107] [111]
50	Richard Maclin	[5] [17] [21] [23] [35] [41] [42] [77] [80] [81] [86] [87] [89] [90] [94] [96] [106] [108] [112] [118]
51	Olvi L. Mangasarian (O. L. Mangasarian)	[60] [68] [69]
52	Marta Mattoso (Marta L. Queiros Mattoso)	[66]
53	Kathleen B. McKusick	[7]
54	Michael Molla	[58] [61] [62] [70] [76]
55	Raymond J. Mooney	[7] [8] [14]
56	Mark A. Musen	[59]
57	Houssam Nassif	[104] [109]
58	Sriraam Natarajan	[102] [103] [107] [108] [110] [111] [120] [121] [122]
59	Feng Niu	[115] [116] [117]
60	Michiel O. Noordewier	[12] [13]
61	Emile F. Nuwaysir	[62]
62	Ciaran O'Reilly	[108]
63	Louis Oliphant	[73] [82] [91] [101] [105]
64	David W. Opitz	[25] [34] [37] [38] [43] [46] [48]
65	C. David Page Jr. (David Page)	[55] [56] [63] [65] [67] [70] [78] [79] [104] [105] [108] [109] [119]
66	George N. Phillips	[71] [84] [93] [99]
67	George N. Phillips Jr.	[88]
68	Raghu Ramakrishnan	[78] [79] [83] [98]
69	Jan Ramon	[97]
70	W. Harmon Ray	[16] [19]
71	Christopher Ré (Christopher Re)	[115] [116] [117]
72	Todd Richmond	[76]
73	Rómer Rosales	[114]
74	Gary M. Scott	[16] [19]
75	David B. Searls	[28] [32] [36]
76	Amina Shabbeer	[112]
77	Mark Shavlik	[72]
78	Kazuhiko Shinki	[105]
79	Steven Smith	[76]
80	Jack Solock	[53]
81	Ameet Soni	[88] [93] [99] [113] [123]
82	William R. Swartout	[52]
83	Prasad Tadepalli	[95] [97] [103] [107] [110] [111] [120]
84	Pradeep Tamma	[83] [98]
85	J. B. Tobler	[62]
86	Lisa Torrey	[77] [80] [81] [86] [87] [89] [90] [94] [96] [100] [106]
87	Geoffrey G. Towell	[4] [7] [8] [12] [13] [14] [15] [18] [20] [22] [31]
88	Michael Waddell	[67] [70]
89	Trevor Walker	[77] [80] [81] [86] [87] [89] [90] [94] [96] [106] [108] [119]
90	Edward W. Wild	[69] [81] [94]
91	Ryan W. Woods	[104] [105]
92	Shipeng Yu	[114]
93	Gerson Zaverucha	[66]
94	Ce Zhang	[116]

Colors in the list of coauthors

Last update Fri May 25 01:42:58 2012 CET by the DBLP Team — Data released under the ODC-BY 1.0 license — See also our legal information page