Raymond J. Mooney

Sindhu Raghavan, Raymond J. Mooney, Hyeonseo Ku: Learning to "Read Between the Lines" using Bayesian Logic Programs. ACL (1) 2012: 349-358

Raymond J. Mooney: Learning Language from Perceptual Context. EACL 2012: 602

Tanvi S. Motwani, Raymond J. Mooney: Improving Video Activity Recognition using Object Recognition and Text Mining. ECAI 2012: 600-605

Joohyun Kim, Raymond J. Mooney: Unsupervised PCFG Induction for Grounded Language Learning with Highly Ambiguous Supervision. EMNLP-CoNLL 2012: 433-444

David L. Chen, Raymond J. Mooney: Learning to Interpret Natural Language Navigation Instructions from Observations. AAAI 2011

Parag Singla, Raymond J. Mooney: Abductive Markov Logic for Plan Recognition. AAAI 2011

Joseph Reisinger, Raymond J. Mooney: Cross-Cutting Models of Lexical Semantics. EMNLP 2011: 1405-1415

Raymond J. Mooney: Learning Language from Its Perceptual Context. PADL 2011: 2-4

Tuyen N. Huynh, Raymond J. Mooney: Online Structure Learning for Markov Logic Networks. ECML/PKDD (2) 2011: 81-96

Sindhu Raghavan, Raymond J. Mooney: Abductive Plan Recognition by Extending Bayesian Logic Programs. ECML/PKDD (2) 2011: 629-644

Tuyen N. Huynh, Raymond J. Mooney: Online Max-Margin Weight Learning for Markov Logic Networks. SDM 2011: 642-651

Cynthia A. Thompson, Raymond J. Mooney: Acquiring Word-Meaning Mappings for Natural Language Interfaces. CoRR abs/1106.4571 (2011)

David L. Chen, Joohyun Kim, Raymond J. Mooney: Training a Multilingual Sportscaster: Using Perceptual Context to Learn Language. J. Artif. Intell. Res. (JAIR) 37: 397-435 (2010)

Sonal Gupta, Raymond J. Mooney: Using Closed Captions as Supervision for Video Activity Recognition. AAAI 2010

Tuyen N. Huynh, Raymond J. Mooney: Online Max-Margin Weight Learning with Markov Logic Networks. Statistical Relational Artificial Intelligence 2010

Sindhu Raghavan, Raymond J. Mooney: Bayesian Abductive Logic Programs. Statistical Relational Artificial Intelligence 2010

Sindhu Raghavan, Adriana Kovashka, Raymond J. Mooney: Authorship Attribution Using Probabilistic Context-Free Grammars. ACL (Short Papers) 2010: 38-42

Joohyun Kim, Raymond J. Mooney: Generative Alignment and Semantic Parsing for Learning from Ambiguous Supervision. COLING (Posters) 2010: 543-551

Rohit J. Kate, Xiaoqiang Luo, Siddharth Patwardhan, Martin Franz, Radu Florian, Raymond J. Mooney, Salim Roukos, Chris Welty: Learning to Predict Readability using Diverse Linguistic Features. COLING 2010: 546-554

Joseph Reisinger, Raymond J. Mooney: A Mixture Model with Sharing for Lexical Semantics. EMNLP 2010: 1173-1182

Joseph Reisinger, Austin Waters, Bryan Silverthorn, Raymond J. Mooney: Spherical Topic Models. ICML 2010: 903-910

Joseph Reisinger, Raymond J. Mooney: Multi-Prototype Vector-Space Models of Word Meaning. HLT-NAACL 2010: 109-117

Brian Kulis, Sugato Basu, Inderjit S. Dhillon, Raymond J. Mooney: Semi-supervised graph clustering: a kernel approach. Machine Learning 74(1): 1-22 (2009)

Ruifang Ge, Raymond J. Mooney: Learning a Compositional Semantic Parser using an Existing Syntactic Parser. ACL/IJCNLP 2009: 611-619

Lilyana Mihalkova, Raymond J. Mooney: Transfer Learning from Minimal Target Data by Mapping across Relational Domains. IJCAI 2009: 1163-1168

Lilyana Mihalkova, Raymond J. Mooney: Learning to Disambiguate Search Queries from Short Sessions. ECML/PKDD (2) 2009: 111-127

Tuyen N. Huynh, Raymond J. Mooney: Max-Margin Weight Learning for Markov Logic Networks. ECML/PKDD (1) 2009: 564-579

Raymond J. Mooney: Learning to Connect Language and Perception. AAAI 2008: 1598-1601

David L. Chen, Raymond J. Mooney: Learning to sportscast: a test of grounded language acquisition. ICML 2008: 128-135

Tuyen N. Huynh, Raymond J. Mooney: Discriminative structure and parameter learning for Markov logic networks. ICML 2008: 416-423

Raymond J. Mooney: Learning Language from Its Perceptual Context. ECML/PKDD (1) 2008: 5

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

Raymond J. Mooney: Transfer Learning by Mapping and Revising Relational Knowledge. SBIA 2008: 2-3

Raymond J. Mooney: Text Mining. SBIA 2008: 6

Lilyana Mihalkova, Tuyen N. Huynh, Raymond J. Mooney: Mapping and Revising Markov Logic Networks for Transfer Learning. AAAI 2007: 608-614

Rohit J. Kate, Raymond J. Mooney: Learning Language Semantics from Ambiguous Supervision. AAAI 2007: 895-900

Razvan C. Bunescu, Raymond J. Mooney: Learning to Extract Relations from the Web using Minimal Supervision. ACL 2007

Yuk Wah Wong, Raymond J. Mooney: Learning Synchronous Grammars for Semantic Parsing with Lambda Calculus. ACL 2007

Raymond J. Mooney: Learning for Semantic Parsing. CICLing 2007: 311-324

Razvan C. Bunescu, Raymond J. Mooney: Multiple instance learning for sparse positive bags. ICML 2007: 105-112

Lilyana Mihalkova, Raymond J. Mooney: Bottom-up learning of Markov logic network structure. ICML 2007: 625-632

Rohit J. Kate, Raymond J. Mooney: Semi-Supervised Learning for Semantic Parsing using Support Vector Machines. HLT-NAACL (Short Papers) 2007: 81-84

Yuk Wah Wong, Raymond J. Mooney: Generation by Inverting a Semantic Parser that Uses Statistical Machine Translation. HLT-NAACL 2007: 172-179

Ruifang Ge, Raymond J. Mooney: Discriminative Reranking for Semantic Parsing. ACL 2006

Rohit J. Kate, Raymond J. Mooney: Using String-Kernels for Learning Semantic Parsers. ACL 2006

Lilyana Mihalkova, Raymond J. Mooney: Using Active Relocation to Aid Reinforcement Learning. FLAIRS Conference 2006: 580-585

Stewart M. Yang, Jianping Song, Harish Rajamani, Tae Won Cho, Yin Zhang, Raymond J. Mooney: Fast and Effective Worm Fingerprinting via Machine Learning. ICAC 2006: 311-313

Mikhail Bilenko, Beena Kamath, Raymond J. Mooney: Adaptive Blocking: Learning to Scale Up Record Linkage. ICDM 2006: 87-96

Yuk Wah Wong, Raymond J. Mooney: Learning for Semantic Parsing with Statistical Machine Translation. HLT-NAACL 2006

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)

Prem Melville, Raymond J. Mooney: Creating diversity in ensembles using artificial data. Information Fusion 6(1): 99-111 (2005)

Raymond J. Mooney, Razvan C. Bunescu: Mining knowledge from text using information extraction. SIGKDD Explorations 7(1): 3-10 (2005)

Rohit J. Kate, Yuk Wah Wong, Raymond J. Mooney: Learning to Transform Natural to Formal Languages. AAAI 2005: 1062-1068

Prem Melville, Stewart M. Yang, Maytal Saar-Tsechansky, Raymond J. Mooney: Active Learning for Probability Estimation Using Jensen-Shannon Divergence. ECML 2005: 268-279

Yuk Lai Suen, Prem Melville, Raymond J. Mooney: Combining Bias and Variance Reduction Techniques for Regression Trees. ECML 2005: 741-749

Jonathan Wildstrom, Peter Stone, Emmett Witchel, Raymond J. Mooney, Michael Dahlin: Towards Self-Configuring Hardware for Distributed Computer Systems. ICAC 2005: 241-249

Prem Melville, Foster J. Provost, Raymond J. Mooney: An Expected Utility Approach to Active Feature-Value Acquisition. ICDM 2005: 745-748

Brian Kulis, Sugato Basu, Inderjit S. Dhillon, Raymond J. Mooney: Semi-supervised graph clustering: a kernel approach. ICML 2005: 457-464

Arindam Banerjee, Chase Krumpelman, Joydeep Ghosh, Sugato Basu, Raymond J. Mooney: Model-based overlapping clustering. KDD 2005: 532-537

Razvan C. Bunescu, Raymond J. Mooney: A Shortest Path Dependency Kernel for Relation Extraction. HLT/EMNLP 2005

Razvan C. Bunescu, Raymond J. Mooney: Subsequence Kernels for Relation Extraction. NIPS 2005

Razvan C. Bunescu, Raymond J. Mooney: Collective Information Extraction with Relational Markov Networks. ACL 2004: 438-445

Prem Melville, Maytal Saar-Tsechansky, Foster J. Provost, Raymond J. Mooney: Active Feature-Value Acquisition for Classifier Induction. ICDM 2004: 483-486

Mikhail Bilenko, Sugato Basu, Raymond J. Mooney: Integrating constraints and metric learning in semi-supervised clustering. ICML 2004

Prem Melville, Raymond J. Mooney: Diverse ensembles for active learning. ICML 2004

Sugato Basu, Mikhail Bilenko, Raymond J. Mooney: A probabilistic framework for semi-supervised clustering. KDD 2004: 59-68

Prem Melville, Nishit Shah, Lilyana Mihalkova, Raymond J. Mooney: Experiments on Ensembles with Missing and Noisy Data. Multiple Classifier Systems 2004: 293-302

Sugato Basu, Arindam Banerjee, Raymond J. Mooney: Active Semi-Supervision for Pairwise Constrained Clustering. SDM 2004

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)

Cynthia A. Thompson, Raymond J. Mooney: Acquiring Word-Meaning Mappings for Natural Language Interfaces. J. Artif. Intell. Res. (JAIR) 18: 1-44 (2003)

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)

Mikhail Bilenko, Raymond J. Mooney: Employing Trainable String Similarity Metrics for Information Integration. IIWeb 2003: 67-72

Prem Melville, Raymond J. Mooney: Constructing Diverse Classifier Ensembles using Artificial Training Examples. IJCAI 2003: 505-512

Mikhail Bilenko, Raymond J. Mooney: Adaptive duplicate detection using learnable string similarity measures. KDD 2003: 39-48

Prem Melville, Raymond J. Mooney, Ramadass Nagarajan: Content-Boosted Collaborative Filtering for Improved Recommendations. AAAI/IAAI 2002: 187-192

Un Yong Nahm, Raymond J. Mooney: Mining soft-matching association rules. CIKM 2002: 681-683

Sugato Basu, Arindam Banerjee, Raymond J. Mooney: Semi-supervised Clustering by Seeding. ICML 2002: 27-34

Lappoon R. Tang, Raymond J. Mooney: Using Multiple Clause Constructors in Inductive Logic Programming for Semantic Parsing. ECML 2001: 466-477

Un Yong Nahm, Raymond J. Mooney: Mining Soft-Matching Rules from Textual Data. IJCAI 2001: 979-986

Sugato Basu, Raymond J. Mooney, Krupakar V. Pasupuleti, Joydeep Ghosh: Evaluating the novelty of text-mined rules using lexical knowledge. KDD 2001: 233-238

Un Yong Nahm, Raymond J. Mooney: A Mutually Beneficial Integration of Data Mining and Information Extraction. AAAI/IAAI 2000: 627-632

Raymond J. Mooney, Loriene Roy: Content-based book recommending using learning for text categorization. ACM DL 2000: 195-204

Claire Cardie, Raymond J. Mooney: Guest Editors' Introduction: Machine Learning and Natural Language. Machine Learning 34(1-3): 5-9 (1999)

Mary Elaine Califf, Raymond J. Mooney: Relational Learning of Pattern-Match Rules for Information Extraction. AAAI/IAAI 1999: 328-334

Cynthia A. Thompson, Raymond J. Mooney: Automatic Construction of Semantic Lexicons for Learning Natural Language Interfaces. AAAI/IAAI 1999: 487-493

Cynthia A. Thompson, Mary Elaine Califf, Raymond J. Mooney: Active Learning for Natural Language Parsing and Information Extraction. ICML 1999: 406-414

Raymond J. Mooney: Learning for Semantic Interpretation: Scaling Up without Dumbing Down. Learning Language in Logic 1999: 57-66

Raymond J. Mooney, Loriene Roy: Content-Based Book Recommending Using Learning for Text Categorization. CoRR cs.DL/9902011 (1999)

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)

Sowmya Ramachandran, Raymond J. Mooney: Theory Refinement of Bayesian Networks with Hidden Variables. ICML 1998: 454-462

Eric Brill, Raymond J. Mooney: An Overview of Empirical Natural Language Processing. AI Magazine 18(4): 13-24 (1997)

Ulf Hermjakob, Raymond J. Mooney: Learning Parse and Translation Decisions from Examples with Rich Context. ACL 1997: 482-489

Tara A. Estlin, Raymond J. Mooney: Learning to Improve both Efficiency and Quality of Planning. IJCAI 1997: 1227-1233

Ulf Hermjakob, Raymond J. Mooney: Learning Parse and Translation Decisions From Examples With Rich Context. CoRR cmp-lg/9706002 (1997)

Paul T. Baffes, Raymond J. Mooney: A Novel Application of Theory Refinement to Student Modeling. AAAI/IAAI, Vol. 1 1996: 403-408

Tara A. Estlin, Raymond J. Mooney: Multi-Strategy Learning of Search Control for Partial-Order Planning. AAAI/IAAI, Vol. 1 1996: 843-848

Siddarth Subramanian, Raymond J. Mooney: Qualitative Multiple-Fault Diagnosis of Continuous Dynamic Systems Using Behavioral Modes. AAAI/IAAI, Vol. 2 1996: 965-970

John M. Zelle, Raymond J. Mooney: Learning to Parse Database Queries Using Inductive Logic Programming. AAAI/IAAI, Vol. 2 1996: 1050-1055

Raymond J. Mooney: Inductive Logic Programming for Natural Language Processing. Inductive Logic Programming Workshop 1996: 3-22

Raymond J. Mooney: Comparative Experiments on Disambiguating Word Senses: An Illustration of the Role of Bias in Machine Learning. CoRR cmp-lg/9612001 (1996)

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)

Raymond J. Mooney: Encouraging Experimental Results on Learning CNF. Machine Learning 19(1): 79-92 (1995)

Bradley L. Richards, Raymond J. Mooney: Automated Refinement of First-Order Horn-Clause Domain Theories. Machine Learning 19(2): 95-131 (1995)

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

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

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)

Dirk Ourston, Raymond J. Mooney: Theory Refinement Combining Analytical and Empirical Methods. Artif. Intell. 66(2): 273-309 (1994)

Raymond J. Mooney, John M. Zelle: Integrating ILP and EBL. SIGART Bulletin 5(1): 12-21 (1994)

Cynthia A. Thompson, Raymond J. Mooney: Inductive Learning For Abductive Diagnosis. AAAI 1994: 664-669

John M. Zelle, Raymond J. Mooney: Inducing Deterministic Prolog Parsers from Treebanks: A Machine Learning Approach. AAAI 1994: 748-753

J. Jeffrey Mahoney, Raymond J. Mooney: Comparing Methods for Refining Certainty-Factor Rule-Bases. ICML 1994: 173-180

John M. Zelle, Raymond J. Mooney, Joshua B. Konvisser: Combining Top-down and Bottom-up Techniques in Inductive Logic Programming. ICML 1994: 343-351

Paul T. Baffes, Raymond J. Mooney: Extending Theory Refinement to M-of-N Rules. Informatica (Slovenia) 17(4) (1993)

Raymond J. Mooney: Induction Over the Unexplained: Using Overly-General Domain Theories to Aid Concept Learning. Machine Learning 10: 79-110 (1993)

John M. Zelle, Raymond J. Mooney: Learning Semantic Grammars with Constructive Inductive Logic Programming. AAAI 1993: 817-822

John M. Zelle, Raymond J. Mooney: Combining FOIL and EBG to Speed-up Logic Programs. IJCAI 1993: 1106-1113

Paul T. Baffes, Raymond J. Mooney: Symbolic Revision of Theories with M-of-N Rules. IJCAI 1993: 1135-1142

Bradley L. Richards, Raymond J. Mooney: Learning Relations by Pathfinding. AAAI 1992: 50-55

Hwee Tou Ng, Raymond J. Mooney: Abductive Plan Recognition and Diagnosis: A Comprehensive Empirical Evaluation. KR 1992: 499-508

J. Jeffrey Mahoney, Raymond J. Mooney: Combining Neural and Symbolic Learning to Revise Probabilistic Rule Bases. NIPS 1992: 107-114

Jude W. Shavlik, Raymond J. Mooney, Geoffrey G. Towell: Symbolic and Neural Learning Algorithms: An Experimental Comparison. Machine Learning 6: 111-143 (1991)

Hwee Tou Ng, Raymond J. Mooney: An Efficient First-Order Horn-Clause Abduction System Based on the ATMS. AAAI 1991: 494-499

Raymond J. Mooney, Dirk Ourston: Constructive Induction in Theory Refinement. ML 1991: 178-182

Bradley L. Richards, Raymond J. Mooney: First-Order Theory Revision. ML 1991: 447-451

Dirk Ourston, Raymond J. Mooney: Improving Shared Rules in Multiple Category Domain Theories. ML 1991: 534-538

Raymond J. Mooney: Learning Plan Schemata From Observation: Explanation-Based Learning for Plan Recognition. Cognitive Science 14(4): 483-509 (1990)

Hwee Tou Ng, Raymond J. Mooney: On the Role of Coherence in Abductive Explanation. AAAI 1990: 337-342

Dirk Ourston, Raymond J. Mooney: Changing the Rules: A Comprehensive Approach to Theory Refinement. AAAI 1990: 815-820

Bruce W. Porter, Raymond J. Mooney (Eds.): Machine Learning, Proceedings of the Seventh International Conference on Machine Learning, Austin, Texas, USA, June 21-23, 1990. Morgan Kaufmann 1990, isbn 1-55860-141-4

Raymond J. Mooney, Dirk Ourston: Induction Over the Unexplained: Integrated Learning of Concepts with Both Explainable and Conventional Aspects. ML 1989: 5-7

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

Raymond J. Mooney: The Effect of Rule Use on the Utility of Explanation-Based Learning. IJCAI 1989: 725-730

Raymond J. Mooney, Jude W. Shavlik, Geoffrey G. Towell, Alan Gove: An Experimental Comparison of Symbolic and Connectionist Learning Algorithms. IJCAI 1989: 775-780

Raymond J. Mooney: Generalizing the Order of Operators in Macro-Operators. ML 1988: 270-283

Gerald DeJong, Raymond J. Mooney: Explanation-Based Learning: An Alternative View. Machine Learning 1(2): 145-176 (1986)

Raymond J. Mooney, Scott Bennett: A Domain Independent Explanation-Based Generalizer. AAAI 1986: 551-555

Raymond J. Mooney, Gerald DeJong: Learning Schemata for Natural Language Processing. IJCAI 1985: 681-687