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Raymond J. Mooney

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2008
108 Raymond J. Mooney: Learning to Connect Language and Perception. AAAI 2008: 1598-1601
107EESonal Gupta, Joohyun Kim, Kristen Grauman, Raymond J. Mooney: Watch, Listen & Learn: Co-training on Captioned Images and Videos. ECML/PKDD (1) 2008: 457-472
106EERaymond J. Mooney: Learning Language from Its Perceptual Context. ECML/PKDD (1) 2008: 5
105EEDavid L. Chen, Raymond J. Mooney: Learning to sportscast: a test of grounded language acquisition. ICML 2008: 128-135
104EETuyen N. Huynh, Raymond J. Mooney: Discriminative structure and parameter learning for Markov logic networks. ICML 2008: 416-423
103EERaymond J. Mooney: Transfer Learning by Mapping and Revising Relational Knowledge. SBIA 2008: 2-3
102EERaymond J. Mooney: Text Mining. SBIA 2008: 6
2007
101 Lilyana Mihalkova, Tuyen N. Huynh, Raymond J. Mooney: Mapping and Revising Markov Logic Networks for Transfer Learning. AAAI 2007: 608-614
100 Rohit J. Kate, Raymond J. Mooney: Learning Language Semantics from Ambiguous Supervision. AAAI 2007: 895-900
99EEYuk Wah Wong, Raymond J. Mooney: Learning Synchronous Grammars for Semantic Parsing with Lambda Calculus. ACL 2007
98EERazvan C. Bunescu, Raymond J. Mooney: Learning to Extract Relations from the Web using Minimal Supervision. ACL 2007
97EERaymond J. Mooney: Learning for Semantic Parsing. CICLing 2007: 311-324
96EEYuk Wah Wong, Raymond J. Mooney: Generation by Inverting a Semantic Parser that Uses Statistical Machine Translation. HLT-NAACL 2007: 172-179
95EERohit J. Kate, Raymond J. Mooney: Semi-Supervised Learning for Semantic Parsing using Support Vector Machines. HLT-NAACL (Short Papers) 2007: 81-84
94EERazvan C. Bunescu, Raymond J. Mooney: Multiple instance learning for sparse positive bags. ICML 2007: 105-112
93EELilyana Mihalkova, Raymond J. Mooney: Bottom-up learning of Markov logic network structure. ICML 2007: 625-632
2006
92EERuifang Ge, Raymond J. Mooney: Discriminative Reranking for Semantic Parsing. ACL 2006
91EERohit J. Kate, Raymond J. Mooney: Using String-Kernels for Learning Semantic Parsers. ACL 2006
90 Lilyana Mihalkova, Raymond J. Mooney: Using Active Relocation to Aid Reinforcement Learning. FLAIRS Conference 2006: 580-585
89EEYuk Wah Wong, Raymond J. Mooney: Learning for Semantic Parsing with Statistical Machine Translation. HLT-NAACL 2006
88EEMikhail Bilenko, Beena Kamath, Raymond J. Mooney: Adaptive Blocking: Learning to Scale Up Record Linkage. ICDM 2006: 87-96
2005
87 Rohit J. Kate, Yuk Wah Wong, Raymond J. Mooney: Learning to Transform Natural to Formal Languages. AAAI 2005: 1062-1068
86EEPrem Melville, Stewart M. Yang, Maytal Saar-Tsechansky, Raymond J. Mooney: Active Learning for Probability Estimation Using Jensen-Shannon Divergence. ECML 2005: 268-279
85EEYuk Lai Suen, Prem Melville, Raymond J. Mooney: Combining Bias and Variance Reduction Techniques for Regression Trees. ECML 2005: 741-749
84EERazvan C. Bunescu, Raymond J. Mooney: A Shortest Path Dependency Kernel for Relation Extraction. HLT/EMNLP 2005
83EEJonathan Wildstrom, Peter Stone, Emmett Witchel, Raymond J. Mooney, Michael Dahlin: Towards Self-Configuring Hardware for Distributed Computer Systems. ICAC 2005: 241-249
82EEPrem Melville, Foster J. Provost, Raymond J. Mooney: An Expected Utility Approach to Active Feature-Value Acquisition. ICDM 2005: 745-748
81EEBrian Kulis, Sugato Basu, Inderjit S. Dhillon, Raymond J. Mooney: Semi-supervised graph clustering: a kernel approach. ICML 2005: 457-464
80EEArindam Banerjee, Chase Krumpelman, Joydeep Ghosh, Sugato Basu, Raymond J. Mooney: Model-based overlapping clustering. KDD 2005: 532-537
79EERazvan C. Bunescu, Raymond J. Mooney: Subsequence Kernels for Relation Extraction. NIPS 2005
78EERazvan C. Bunescu, Ruifang Ge, Rohit J. Kate, Edward M. Marcotte, Raymond J. Mooney, Arun K. Ramani, Yuk Wah Wong: Comparative experiments on learning information extractors for proteins and their interactions. Artificial Intelligence in Medicine 33(2): 139-155 (2005)
77EEPrem Melville, Raymond J. Mooney: Creating diversity in ensembles using artificial data. Information Fusion 6(1): 99-111 (2005)
76EERaymond J. Mooney, Razvan C. Bunescu: Mining knowledge from text using information extraction. SIGKDD Explorations 7(1): 3-10 (2005)
2004
75EERazvan C. Bunescu, Raymond J. Mooney: Collective Information Extraction with Relational Markov Networks. ACL 2004: 438-445
74EEPrem Melville, Maytal Saar-Tsechansky, Foster J. Provost, Raymond J. Mooney: Active Feature-Value Acquisition for Classifier Induction. ICDM 2004: 483-486
73EEPrem Melville, Raymond J. Mooney: Diverse ensembles for active learning. ICML 2004
72EEMikhail Bilenko, Sugato Basu, Raymond J. Mooney: Integrating constraints and metric learning in semi-supervised clustering. ICML 2004
71EESugato Basu, Mikhail Bilenko, Raymond J. Mooney: A probabilistic framework for semi-supervised clustering. KDD 2004: 59-68
70EEPrem Melville, Nishit Shah, Lilyana Mihalkova, Raymond J. Mooney: Experiments on Ensembles with Missing and Noisy Data. Multiple Classifier Systems 2004: 293-302
69EESugato Basu, Arindam Banerjee, Raymond J. Mooney: Active Semi-Supervision for Pairwise Constrained Clustering. SDM 2004
2003
68EEMikhail Bilenko, Raymond J. Mooney: Employing Trainable String Similarity Metrics for Information Integration. IIWeb 2003: 67-72
67 Prem Melville, Raymond J. Mooney: Constructing Diverse Classifier Ensembles using Artificial Training Examples. IJCAI 2003: 505-512
66EEMikhail Bilenko, Raymond J. Mooney: Adaptive duplicate detection using learnable string similarity measures. KDD 2003: 39-48
65EEMikhail Bilenko, Raymond J. Mooney, William W. Cohen, Pradeep Ravikumar, Stephen E. Fienberg: Adaptive Name Matching in Information Integration. IEEE Intelligent Systems 18(5): 16-23 (2003)
64EECynthia A. Thompson, Raymond J. Mooney: Acquiring Word-Meaning Mappings for Natural Language Interfaces. J. Artif. Intell. Res. (JAIR) 18: 1-44 (2003)
63EEMary Elaine Califf, Raymond J. Mooney: Bottom-Up Relational Learning of Pattern Matching Rules for Information Extraction. Journal of Machine Learning Research 4: 177-210 (2003)
2002
62 Prem Melville, Raymond J. Mooney, Ramadass Nagarajan: Content-Boosted Collaborative Filtering for Improved Recommendations. AAAI/IAAI 2002: 187-192
61EEUn Yong Nahm, Raymond J. Mooney: Mining soft-matching association rules. CIKM 2002: 681-683
60 Sugato Basu, Arindam Banerjee, Raymond J. Mooney: Semi-supervised Clustering by Seeding. ICML 2002: 27-34
2001
59EELappoon R. Tang, Raymond J. Mooney: Using Multiple Clause Constructors in Inductive Logic Programming for Semantic Parsing. ECML 2001: 466-477
58 Un Yong Nahm, Raymond J. Mooney: Mining Soft-Matching Rules from Textual Data. IJCAI 2001: 979-986
57EESugato Basu, Raymond J. Mooney, Krupakar V. Pasupuleti, Joydeep Ghosh: Evaluating the novelty of text-mined rules using lexical knowledge. KDD 2001: 233-238
2000
56 Un Yong Nahm, Raymond J. Mooney: A Mutually Beneficial Integration of Data Mining and Information Extraction. AAAI/IAAI 2000: 627-632
55EERaymond J. Mooney, Loriene Roy: Content-based book recommending using learning for text categorization. ACM DL 2000: 195-204
1999
54 Mary Elaine Califf, Raymond J. Mooney: Relational Learning of Pattern-Match Rules for Information Extraction. AAAI/IAAI 1999: 328-334
53 Cynthia A. Thompson, Raymond J. Mooney: Automatic Construction of Semantic Lexicons for Learning Natural Language Interfaces. AAAI/IAAI 1999: 487-493
52 Cynthia A. Thompson, Mary Elaine Califf, Raymond J. Mooney: Active Learning for Natural Language Parsing and Information Extraction. ICML 1999: 406-414
51EERaymond J. Mooney: Learning for Semantic Interpretation: Scaling Up without Dumbing Down. Learning Language in Logic 1999: 57-66
50EERaymond J. Mooney, Loriene Roy: Content-Based Book Recommending Using Learning for Text Categorization CoRR cs.DL/9902011: (1999)
49 Claire Cardie, Raymond J. Mooney: Guest Editors' Introduction: Machine Learning and Natural Language. Machine Learning 34(1-3): 5-9 (1999)
1998
48 Sowmya Ramachandran, Raymond J. Mooney: Theory Refinement of Bayesian Networks with Hidden Variables. ICML 1998: 454-462
47 Mary Elaine Califf, Raymond J. Mooney: Advantages of Decision Lists and Implicit Negatives in Inductive Logic Programming. New Generation Comput. 16(3): 263-281 (1998)
1997
46 Ulf Hermjakob, Raymond J. Mooney: Learning Parse and Translation Decisions from Examples with Rich Context. ACL 1997: 482-489
45 Tara A. Estlin, Raymond J. Mooney: Learning to Improve both Efficiency and Quality of Planning. IJCAI 1997: 1227-1233
44 Eric Brill, Raymond J. Mooney: An Overview of Empirical Natural Language Processing. AI Magazine 18(4): 13-24 (1997)
43EEUlf Hermjakob, Raymond J. Mooney: Learning Parse and Translation Decisions From Examples With Rich Context CoRR cmp-lg/9706002: (1997)
1996
42 Paul T. Baffes, Raymond J. Mooney: A Novel Application of Theory Refinement to Student Modeling. AAAI/IAAI, Vol. 1 1996: 403-408
41 Tara A. Estlin, Raymond J. Mooney: Multi-Strategy Learning of Search Control for Partial-Order Planning. AAAI/IAAI, Vol. 1 1996: 843-848
40 John M. Zelle, Raymond J. Mooney: Learning to Parse Database Queries Using Inductive Logic Programming. AAAI/IAAI, Vol. 2 1996: 1050-1055
39 Siddarth Subramanian, Raymond J. Mooney: Qualitative Multiple-Fault Diagnosis of Continuous Dynamic Systems Using Behavioral Modes. AAAI/IAAI, Vol. 2 1996: 965-970
38 Raymond J. Mooney: Inductive Logic Programming for Natural Language Processing. Inductive Logic Programming Workshop 1996: 3-22
37EERaymond J. Mooney: Comparative Experiments on Disambiguating Word Senses: An Illustration of the Role of Bias in Machine Learning CoRR cmp-lg/9612001: (1996)
1995
36 John M. Zelle, Raymond J. Mooney: Comparative results on using inductive logic programming for corpus-based parser construction. Learning for Natural Language Processing 1995: 355-369
35 Raymond J. Mooney, Mary Elaine Califf: Learning the past tense of English verbs using inductive logic programming. Learning for Natural Language Processing 1995: 370-384
34EERaymond J. Mooney, Mary Elaine Califf: Induction of First-Order Decision Lists: Results on Learning the Past Tense of English Verbs CoRR abs/cs/9506102: (1995)
33 Raymond J. Mooney, Mary Elaine Califf: Induction of First-Order Decision Lists: Results on Learning the Past Tense of English Verbs. J. Artif. Intell. Res. (JAIR) 3: 1-24 (1995)
32 Raymond J. Mooney: Encouraging Experimental Results on Learning CNF. Machine Learning 19(1): 79-92 (1995)
31 Bradley L. Richards, Raymond J. Mooney: Automated Refinement of First-Order Horn-Clause Domain Theories. Machine Learning 19(2): 95-131 (1995)
1994
30 Cynthia A. Thompson, Raymond J. Mooney: Inductive Learning For Abductive Diagnosis. AAAI 1994: 664-669
29 John M. Zelle, Raymond J. Mooney: Inducing Deterministic Prolog Parsers from Treebanks: A Machine Learning Approach. AAAI 1994: 748-753
28 J. Jeffrey Mahoney, Raymond J. Mooney: Comparing Methods for Refining Certainty-Factor Rule-Bases. ICML 1994: 173-180
27 John M. Zelle, Raymond J. Mooney, Joshua B. Konvisser: Combining Top-down and Bottom-up Techniques in Inductive Logic Programming. ICML 1994: 343-351
26 Dirk Ourston, Raymond J. Mooney: Theory Refinement Combining Analytical and Empirical Methods. Artif. Intell. 66(2): 273-309 (1994)
25 Raymond J. Mooney, John M. Zelle: Integrating ILP and EBL. SIGART Bulletin 5(1): 12-21 (1994)
1993
24 John M. Zelle, Raymond J. Mooney: Learning Semantic Grammars with Constructive Inductive Logic Programming. AAAI 1993: 817-822
23 John M. Zelle, Raymond J. Mooney: Combining FOIL and EBG to Speed-up Logic Programs. IJCAI 1993: 1106-1113
22 Paul T. Baffes, Raymond J. Mooney: Symbolic Revision of Theories with M-of-N Rules. IJCAI 1993: 1135-1142
21 Paul T. Baffes, Raymond J. Mooney: Extending Theory Refinement to M-of-N Rules. Informatica (Slovenia) 17(4): (1993)
20 Raymond J. Mooney: Induction Over the Unexplained: Using Overly-General Domain Theories to Aid Concept Learning. Machine Learning 10: 79-110 (1993)
1992
19 Bradley L. Richards, Raymond J. Mooney: Learning Relations by Pathfinding. AAAI 1992: 50-55
18 Hwee Tou Ng, Raymond J. Mooney: Abductive Plan Recognition and Diagnosis: A Comprehensive Empirical Evaluation. KR 1992: 499-508
17EEJ. Jeffrey Mahoney, Raymond J. Mooney: Combining Neural and Symbolic Learning to Revise Probabilistic Rule Bases. NIPS 1992: 107-114
1991
16 Hwee Tou Ng, Raymond J. Mooney: An Efficient First-Order Horn-Clause Abduction System Based on the ATMS. AAAI 1991: 494-499
15 Raymond J. Mooney, Dirk Ourston: Constructive Induction in Theory Refinement. ML 1991: 178-182
14 Bradley L. Richards, Raymond J. Mooney: First-Order Theory Revision. ML 1991: 447-451
13 Dirk Ourston, Raymond J. Mooney: Improving Shared Rules in Multiple Category Domain Theories. ML 1991: 534-538
12 Jude W. Shavlik, Raymond J. Mooney, Geoffrey G. Towell: Symbolic and Neural Learning Algorithms: An Experimental Comparison. Machine Learning 6: 111-143 (1991)
1990
11 Hwee Tou Ng, Raymond J. Mooney: On the Role of Coherence in Abductive Explanation. AAAI 1990: 337-342
10 Dirk Ourston, Raymond J. Mooney: Changing the Rules: A Comprehensive Approach to Theory Refinement. AAAI 1990: 815-820
9 Raymond J. Mooney: Learning Plan Schemata From Observation: Explanation-Based Learning for Plan Recognition. Cognitive Science 14(4): 483-509 (1990)
1989
8 Raymond J. Mooney: The Effect of Rule Use on the Utility of Explanation-Based Learning. IJCAI 1989: 725-730
7 Raymond J. Mooney, Jude W. Shavlik, Geoffrey G. Towell, Alan Gove: An Experimental Comparison of Symbolic and Connectionist Learning Algorithms. IJCAI 1989: 775-780
6 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
5 Raymond J. Mooney, Dirk Ourston: Induction Over the Unexplained: Integrated Learning of Concepts with Both Explainable and Conventional Aspects. ML 1989: 5-7
1988
4 Raymond J. Mooney: Generalizing the Order of Operators in Macro-Operators. ML 1988: 270-283
1986
3 Raymond J. Mooney, Scott Bennett: A Domain Independent Explanation-Based Generalizer. AAAI 1986: 551-555
2 Gerald DeJong, Raymond J. Mooney: Explanation-Based Learning: An Alternative View. Machine Learning 1(2): 145-176 (1986)
1985
1 Raymond J. Mooney, Gerald DeJong: Learning Schemata for Natural Language Processing. IJCAI 1985: 681-687

Coauthor Index

1Paul T. Baffes [21] [22] [42]
2Arindam Banerjee [60] [69] [80]
3Sugato Basu [57] [60] [69] [71] [72] [80] [81]
4Scott Bennett [3]
5Mikhail Bilenko [65] [66] [68] [71] [72] [88]
6Eric Brill [44]
7Razvan C. Bunescu [75] [76] [78] [79] [84] [94] [98]
8Mary Elaine Califf [33] [34] [35] [47] [52] [54] [63]
9Claire Cardie [49]
10David L. Chen [105]
11William W. Cohen [65]
12Michael Dahlin [83]
13Gerald DeJong [1] [2]
14Inderjit S. Dhillon [81]
15Tara A. Estlin [41] [45]
16Stephen E. Fienberg [65]
17Douglas H. Fisher [6]
18Ruifang Ge [78] [92]
19Joydeep Ghosh [57] [80]
20Alan Gove [7]
21Kristen Grauman [107]
22Sonal Gupta [107]
23Ulf Hermjakob [43] [46]
24Tuyen N. Huynh [101] [104]
25Beena Kamath [88]
26Rohit J. Kate [78] [87] [91] [95] [100]
27Joohyun Kim [107]
28Joshua B. Konvisser [27]
29Chase Krumpelman [80]
30Brian Kulis [81]
31J. Jeffrey Mahoney [17] [28]
32Edward M. Marcotte [78]
33Kathleen B. McKusick [6]
34Prem Melville [62] [67] [70] [73] [74] [77] [82] [85] [86]
35Lilyana Mihalkova [70] [90] [93] [101]
36Ramadass Nagarajan [62]
37Un Yong Nahm [56] [58] [61]
38Hwee Tou Ng [11] [16] [18]
39Dirk Ourston [5] [10] [13] [15] [26]
40Krupakar V. Pasupuleti [57]
41Foster J. Provost [74] [82]
42Sowmya Ramachandran [48]
43Arun K. Ramani [78]
44Pradeep Ravikumar [65]
45Bradley L. Richards [14] [19] [31]
46Loriene Roy [50] [55]
47Maytal Saar-Tsechansky [74] [86]
48Nishit Shah [70]
49Jude W. Shavlik [6] [7] [12]
50Peter Stone [83]
51Siddarth Subramanian [39]
52Yuk Lai Suen [85]
53Lappoon R. Tang [59]
54Cynthia A. Thompson [30] [52] [53] [64]
55Geoffrey G. Towell [6] [7] [12]
56Jonathan Wildstrom [83]
57Emmett Witchel [83]
58Yuk Wah Wong [78] [87] [89] [96] [99]
59Stewart M. Yang [86]
60John M. Zelle [23] [24] [25] [27] [29] [36] [40]

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Copyright © Sun May 17 03:24:02 2009 by Michael Ley (ley@uni-trier.de)