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