Raymond J. Mooney

	2009
111		Tuyen N. Huynh, Raymond J. Mooney: Max-Margin Weight Learning for Markov Logic Networks. ECML/PKDD (1) 2009: 564-579
110		Lilyana Mihalkova, Raymond J. Mooney: Learning to Disambiguate Search Queries from Short Sessions. ECML/PKDD (2) 2009: 111-127
109		Lilyana Mihalkova, Raymond J. Mooney: Transfer Learning from Minimal Target Data by Mapping across Relational Domains. IJCAI 2009: 1163-1168
	2008
108		Raymond J. Mooney: Learning to Connect Language and Perception. AAAI 2008: 1598-1601
107		Sonal Gupta, Joohyun Kim, Kristen Grauman, Raymond J. Mooney: Watch, Listen & Learn: Co-training on Captioned Images and Videos. ECML/PKDD (1) 2008: 457-472
106		Raymond J. Mooney: Learning Language from Its Perceptual Context. ECML/PKDD (1) 2008: 5
105		David L. Chen, Raymond J. Mooney: Learning to sportscast: a test of grounded language acquisition. ICML 2008: 128-135
104		Tuyen N. Huynh, Raymond J. Mooney: Discriminative structure and parameter learning for Markov logic networks. ICML 2008: 416-423
103		Raymond J. Mooney: Transfer Learning by Mapping and Revising Relational Knowledge. SBIA 2008: 2-3
102		Raymond 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
99		Yuk Wah Wong, Raymond J. Mooney: Learning Synchronous Grammars for Semantic Parsing with Lambda Calculus. ACL 2007
98		Razvan C. Bunescu, Raymond J. Mooney: Learning to Extract Relations from the Web using Minimal Supervision. ACL 2007
97		Raymond J. Mooney: Learning for Semantic Parsing. CICLing 2007: 311-324
96		Yuk Wah Wong, Raymond J. Mooney: Generation by Inverting a Semantic Parser that Uses Statistical Machine Translation. HLT-NAACL 2007: 172-179
95		Rohit J. Kate, Raymond J. Mooney: Semi-Supervised Learning for Semantic Parsing using Support Vector Machines. HLT-NAACL (Short Papers) 2007: 81-84
94		Razvan C. Bunescu, Raymond J. Mooney: Multiple instance learning for sparse positive bags. ICML 2007: 105-112
93		Lilyana Mihalkova, Raymond J. Mooney: Bottom-up learning of Markov logic network structure. ICML 2007: 625-632
	2006
92		Ruifang Ge, Raymond J. Mooney: Discriminative Reranking for Semantic Parsing. ACL 2006
91		Rohit 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
89		Yuk Wah Wong, Raymond J. Mooney: Learning for Semantic Parsing with Statistical Machine Translation. HLT-NAACL 2006
88		Mikhail 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
86		Prem Melville, Stewart M. Yang, Maytal Saar-Tsechansky, Raymond J. Mooney: Active Learning for Probability Estimation Using Jensen-Shannon Divergence. ECML 2005: 268-279
85		Yuk Lai Suen, Prem Melville, Raymond J. Mooney: Combining Bias and Variance Reduction Techniques for Regression Trees. ECML 2005: 741-749
84		Razvan C. Bunescu, Raymond J. Mooney: A Shortest Path Dependency Kernel for Relation Extraction. HLT/EMNLP 2005
83		Jonathan Wildstrom, Peter Stone, Emmett Witchel, Raymond J. Mooney, Michael Dahlin: Towards Self-Configuring Hardware for Distributed Computer Systems. ICAC 2005: 241-249
82		Prem Melville, Foster J. Provost, Raymond J. Mooney: An Expected Utility Approach to Active Feature-Value Acquisition. ICDM 2005: 745-748
81		Brian Kulis, Sugato Basu, Inderjit S. Dhillon, Raymond J. Mooney: Semi-supervised graph clustering: a kernel approach. ICML 2005: 457-464
80		Arindam Banerjee, Chase Krumpelman, Joydeep Ghosh, Sugato Basu, Raymond J. Mooney: Model-based overlapping clustering. KDD 2005: 532-537
79		Razvan C. Bunescu, Raymond J. Mooney: Subsequence Kernels for Relation Extraction. NIPS 2005
78		Razvan 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)
77		Prem Melville, Raymond J. Mooney: Creating diversity in ensembles using artificial data. Information Fusion 6(1): 99-111 (2005)
76		Raymond J. Mooney, Razvan C. Bunescu: Mining knowledge from text using information extraction. SIGKDD Explorations 7(1): 3-10 (2005)
	2004
75		Razvan C. Bunescu, Raymond J. Mooney: Collective Information Extraction with Relational Markov Networks. ACL 2004: 438-445
74		Prem Melville, Maytal Saar-Tsechansky, Foster J. Provost, Raymond J. Mooney: Active Feature-Value Acquisition for Classifier Induction. ICDM 2004: 483-486
73		Prem Melville, Raymond J. Mooney: Diverse ensembles for active learning. ICML 2004
72		Mikhail Bilenko, Sugato Basu, Raymond J. Mooney: Integrating constraints and metric learning in semi-supervised clustering. ICML 2004
71		Sugato Basu, Mikhail Bilenko, Raymond J. Mooney: A probabilistic framework for semi-supervised clustering. KDD 2004: 59-68
70		Prem Melville, Nishit Shah, Lilyana Mihalkova, Raymond J. Mooney: Experiments on Ensembles with Missing and Noisy Data. Multiple Classifier Systems 2004: 293-302
69		Sugato Basu, Arindam Banerjee, Raymond J. Mooney: Active Semi-Supervision for Pairwise Constrained Clustering. SDM 2004
	2003
68		Mikhail 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
66		Mikhail Bilenko, Raymond J. Mooney: Adaptive duplicate detection using learnable string similarity measures. KDD 2003: 39-48
65		Mikhail Bilenko, Raymond J. Mooney, William W. Cohen, Pradeep D. Ravikumar, Stephen E. Fienberg: Adaptive Name Matching in Information Integration. IEEE Intelligent Systems 18(5): 16-23 (2003)
64		Cynthia A. Thompson, Raymond J. Mooney: Acquiring Word-Meaning Mappings for Natural Language Interfaces. J. Artif. Intell. Res. (JAIR) 18: 1-44 (2003)
63		Mary 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
61		Un 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
59		Lappoon 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
57		Sugato 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
55		Raymond 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
51		Raymond J. Mooney: Learning for Semantic Interpretation: Scaling Up without Dumbing Down. Learning Language in Logic 1999: 57-66
50		Raymond 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)
43		Ulf 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
37		Raymond 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
34		Raymond 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
17		J. 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

1	Paul T. Baffes	[21] [22] [42]
2	Arindam Banerjee	[60] [69] [80]
3	Sugato Basu	[57] [60] [69] [71] [72] [80] [81]
4	Scott Bennett	[3]
5	Mikhail Bilenko (Misha Bilenko)	[65] [66] [68] [71] [72] [88]
6	Eric Brill	[44]
7	Razvan C. Bunescu	[75] [76] [78] [79] [84] [94] [98]
8	Mary Elaine Califf	[33] [34] [35] [47] [52] [54] [63]
9	Claire Cardie	[49]
10	David L. Chen	[105]
11	William W. Cohen	[65]
12	Michael Dahlin	[83]
13	Gerald DeJong	[1] [2]
14	Inderjit S. Dhillon	[81]
15	Tara A. Estlin	[41] [45]
16	Stephen E. Fienberg	[65]
17	Douglas H. Fisher	[6]
18	Ruifang Ge	[78] [92]
19	Joydeep Ghosh	[57] [80]
20	Alan Gove	[7]
21	Kristen Grauman	[107]
22	Sonal Gupta	[107]
23	Ulf Hermjakob	[43] [46]
24	Tuyen N. Huynh	[101] [104] [111]
25	Beena Kamath	[88]
26	Rohit J. Kate	[78] [87] [91] [95] [100]
27	Joohyun Kim	[107]
28	Joshua B. Konvisser	[27]
29	Chase Krumpelman	[80]
30	Brian Kulis	[81]
31	J. Jeffrey Mahoney	[17] [28]
32	Edward M. Marcotte	[78]
33	Kathleen B. McKusick	[6]
34	Prem Melville	[62] [67] [70] [73] [74] [77] [82] [85] [86]
35	Lilyana Mihalkova	[70] [90] [93] [101] [109] [110]
36	Ramadass Nagarajan	[62]
37	Un Yong Nahm	[56] [58] [61]
38	Hwee Tou Ng	[11] [16] [18]
39	Dirk Ourston	[5] [10] [13] [15] [26]
40	Krupakar V. Pasupuleti	[57]
41	Foster J. Provost	[74] [82]
42	Sowmya Ramachandran	[48]
43	Arun K. Ramani	[78]
44	Pradeep D. Ravikumar	[65]
45	Bradley L. Richards	[14] [19] [31]
46	Loriene Roy	[50] [55]
47	Maytal Saar-Tsechansky	[74] [86]
48	Nishit Shah	[70]
49	Jude W. Shavlik	[6] [7] [12]
50	Peter Stone	[83]
51	Siddarth Subramanian	[39]
52	Yuk Lai Suen	[85]
53	Lappoon R. Tang	[59]
54	Cynthia A. Thompson	[30] [52] [53] [64]
55	Geoffrey G. Towell	[6] [7] [12]
56	Jonathan Wildstrom	[83]
57	Emmett Witchel	[83]
58	Yuk Wah Wong	[78] [87] [89] [96] [99]
59	Stewart M. Yang	[86]
60	John M. Zelle	[23] [24] [25] [27] [29] [36] [40]

Colors in the list of coauthors