Publications: All Publications

1. Measuring Sound Symbolism in Audio-visual Models
   [Details] [PDF]
   Wei-Cheng Tseng, Yi-Jen Shih, David Harwath, Raymond Mooney
   In IEEE Spoken Language Technology (SLT) Workshop, December 2024.
2. CAT-BENCH: Benchmarking Language Model Understanding of Causal and Temporal Dependencies in Plans
   [Details] [PDF] [Slides (PPT)] [Slides (PDF)] [Video]
   Yash Kumar Lal, Vanya Cohen, Nathanael Chambers, Niranjan Balasubramanian, Raymond Mooney
   Empirical Methods in Natural Language Processing (EMNLP), November 2024.
3. Natural Language Can Help Bridge the Sim2Real Gap
   [Details] [PDF] [Slides (PDF)] [Poster] [Video]
   Albert Yu, Adeline Foote, Raymond Mooney, and Roberto Martín-Martín
   In Robotics, Science and Systems (RSS), July 2024.
4. Multimodal Contextualized Semantic Parsing from Speech
   [Details] [PDF] [Slides (PDF)] [Poster] [Video]
   Jordan Voas, Raymond Mooney, David Harwath
   In Association for Computational Linguistics (ACL), August 2024.
5. A Survey of Robotic Language Grounding: Tradeoffs Between Symbols and Embeddings
   [Details] [PDF] [Slides (PDF)] [Poster]
   Vanya Cohen, Jason Xinyu Liu, Raymond Mooney, Stefanie Tellex, David Watkins
   In International Joint Conference on Artificial Intelligence (IJCAI), August 2024.
6. CONTRADOC: Understanding Self-Contradictions in Documents with Large Language Models
   [Details] [PDF] [Poster]
   Jierui Li, Vipul Raheja, Dhruv Kumar
   In North American Chapter of the Association for Computational Linguistics (NAACL), June 2024.
7. When is Tree Search Useful for LLM Planning? It Depends on the Discriminator
   [Details] [PDF] [Slides (PDF)] [Poster] [Video]
   Ziru Chen, Michael White, Raymond Mooney, Ali Payani, Yu Su, Huan Sun
   In Association for Computational Linguistics (ACL), August 2024.
8. Distilling Algorithmic Reasoning from LLMs via Explaining Solution Programs
   [Details] [PDF]
   Jierui Li and Raymond Mooney
   preprint, April 2024.
9. CAPE: Corrective Actions from Precondition Errors using Large Language Models
   [Details] [PDF]
   Shreyas Sundara Raman, Vanya Cohen, Ifrah Idrees, Eric Rosen, Raymond Mooney, Stefanie Tellex, and David Paulius
   In International Conference on Robotics and Automation (ICRA), May 2024.
10. Sparse Meets Dense: A Hybrid Approach to Enhance Scientific Document Retrieval
    [Details] [PDF] [Slides (PPT)]
    Priyanka Mandikal, Raymond Mooney
    In The 4th Workshop on Scientific Document Understanding, AAAI, February 2024.
11. SAGEViz: SchemA GEneration and Visualization
    [Details] [PDF]
    Sugam Devare, Mahnaz Koupaee, Gautham Gunapati, Sayontan Ghosh, Sai Vallurupalli, Yash Kumar Lal, Francis Ferraro, Nathanael Chambers, Greg Durrett, Raymond Mooney, Katrin Erk, Niranjan Balasubramanian
    In Empirical Methods in Natural Language Processing (EMNLP) Demo Track, December 2023.
12. What is the Best Automated Metric for Text to Motion Generation?
    [Details] [PDF]
    Jordan Voas
    Masters Thesis, Department of Computer Science, UT Austin, Austin, TX, May 2023.
13. What is the Best Automated Metric for Text to Motion Generation?
    [Details] [PDF] [Slides (PPT)] [Video]
    Jordan Voas, Yili Wang, Qixing Huang, Raymond Mooney
    In ACM SIGGRAPH Asia, December 2023.
14. Explaining Competitive-Level Programming Solutions using LLMs
    [Details] [PDF] [Poster]
    Jierui Li, Szymon Tworkowski, Yingying Wu, Raymond Mooney
    In Association of Computational Linguistics (ACL), Natural Language Reasoning and Structured Explanations Workshop, July 2023.
15. Using Planning to Improve Semantic Parsing of Instructional Texts
    [Details] [PDF] [Slides (PDF)]
    Vanya Cohen, Raymond Mooney
    Association of Computational Linguistics (ACL), Natural Language Reasoning and Structured Explanations Workshop, July 2023.
16. Text-to-SQL Error Correction with Language Models of Code
    [Details] [PDF] [Poster]
    Ziru Chen, Shijie Chen, Michael White, Raymond Mooney, Ali Payani, Jayanth Srinivasa, Yu Su, Huan Sun
    In Proceedings of the Association for Computational Linguistics (ACL), January 2023.
17. Directly Optimizing Evaluation Metrics to Improve Text to Motion
    [Details] [PDF]
    Yili Wang
    Masters Thesis, Department of Computer Science, UT Austin, May 2023.
18. Learning Deep Semantics for Test Completion
    [Details] [PDF] [Slides (PDF)]
    Pengyu Nie, Rahul Banerjee, Junyi Jessy Li, Raymond Mooney and Milos Gligoric
    International Conference on Software Engineering, May 2023.
19. Using Both Demonstrations and Language Instructions to Efficiently Learn Robotic Tasks
    [Details] [PDF] [Video]
    Albert Yu, Raymond J. Mooney
    In International Conference on Learning Representations, May 2023.
20. “Female Astronaut: Because sandwiches won’t make themselves up there!": Towards multi-modal misogyny detection in memes
    [Details] [PDF]
    Smriti Singh, Amritha Haridasan, Raymond Mooney
    Association of Computational Linguistics (ACL), Workshop on Online Abuse and Harms (WOAH), July 2023.
21. End-to-End Learning to Follow Language Instructions with Compositional Policies
    [Details] [PDF] [Poster]
    Vanya Cohen, Geraud Nangue Tasse, Nakul Gopalan, Steven James, Ray Mooney, Benjamin Rosman
    In Workshop on Language and Robot Learning at CoRL 2022, December 2022.
22. Planning with Large Language Models via Corrective Re-prompting
    [Details] [PDF]
    Shreyas Sundara Raman, Vanya Cohen, Eric Rosen, Ifrah Idrees, David Paulius, Stefanie Tellex
    In Foundation Models for Decision Making Workshop at NeurIPS 2022, January 2022.
23. Using Developer Discussions to Guide Fixing Bugs in Software
    [Details] [PDF] [Slides (PDF)] [Video]
    Sheena Panthaplackel, Milos Gligoric, Junyi Jessy Li, Raymond J. Mooney
    In Findings of the 2022 Conference on Empirical Methods in Natural Language Processing (EMNLP), December 2022.
24. Incorporating External Information for Visual Question Answering
    [Details] [PDF] [Slides (PDF)]
    Jialin Wu
    PhD Thesis, Department of Computer Science, UT Austin, August 2022.
25. Zero-shot Video Moment Retrieval With Off-the-Shelf Models
    [Details] [PDF] [Poster]
    Anuj Diwan, Puyuan Peng, Raymond J. Mooney
    In Workshop on Transfer Learning for Natural Language Processing at NeurIPS 2022, December 2022.
26. Entity-Focused Dense Passage Retrieval for Outside-Knowledge Visual Question Answering
    [Details] [PDF] [Poster] [Video]
    Jialin Wu, Raymond Mooney
    In Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing (EMNLP), December 2022.
27. Using Natural Language to Aid Task Specification in Sequential Decision Making Problems
    [Details] [PDF] [Slides (PDF)] [Video]
    Prasoon Goyal
    PhD Thesis, Department of Computer Science, UT Austin, July 2022.
28. Facilitating Software Evolution through Natural Language Comments and Dialogue
    [Details] [PDF] [Slides (PDF)]
    Sheena Panthaplackel
    PhD Thesis, Department of Computer Science, UT Austin, August 2022.
29. Using Commonsense Knowledge to Answer Why-Questions
    [Details] [PDF] [Video]
    Yash Kumar Lal, Niket Tandon, Tanvi Aggarwal, Horace Liu, Nathanael Chambers, Raymond Mooney, Niranjan Balasubramanian
    In Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing, December 2022.
30. Updated Headline Generation: Creating Updated Summaries for Evolving News Stories
    [Details] [PDF] [Slides (PDF)] [Poster] [Video]
    Sheena Panthaplackel, Adrian Benton, Mark Dredze
    In Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics, May 2022.
31. Learning to Describe Solutions for Bug Reports Based on Developer Discussions
    [Details] [PDF] [Slides (PDF)] [Poster] [Video]
    Sheena Panthaplackel, Junyi Jessy Li, Milos Gligoric, Raymond J. Mooney
    In Findings of the Annual Meeting of the Association for Computational Linguistics (ACL), May 2022.
32. Impact of Evaluation Methodologies on Code Summarization
    [Details] [PDF] [Slides (PDF)] [Poster] [Video]
    Pengyu Nie and Jiyang Zhang and Junyi Jessy Li and Raymond J. Mooney and Milos Gligoric
    In Annual Meeting of the Association for Computational Linguistics, May 2022.
33. Multi-Modal Answer Validation for Knowledge-Based VQA
    [Details] [PDF] [Video]
    Jialin Wu, Jiasen Lu, Ashish Sabharwal, Roozbeh Mottaghi
    In Proceedings of the AAAI Conference on Artificial Intelligence, February 2022.
34. Towards Automated Error Analysis: Learning to Characterize Errors
    [Details] [PDF] [Poster]
    Tong Gao, Shivang Singh, Raymond J. Mooney
    Short version appears in the 19th International Florida Artificial Intelligence Research Society Conference (FLAIRS), May 2022.
35. TellMeWhy: A Dataset for Answering Why-Questions in Narratives
    [Details] [PDF] [Slides (PDF)] [Video]
    Yash Kumar Lal, Nathanael Chambers, Raymond Mooney, Niranjan Balasubramanian
    In Findings of ACL 2021, August 2021.
36. Zero-shot Task Adaptation using Natural Language
    [Details] [PDF]
    Prasoon Goyal, Raymond J. Mooney, Scott Niekum
    In Arxiv, June 2021.
37. Facilitating Software Evolution through Natural Language Comments and Dialogue
    [Details] [PDF] [Slides (PDF)] [Video]
    Sheena Panthaplackel
    October 2021. Ph.D. Proposal.
38. Using Natural Language to Aid Task Specification in Sequential Decision Making Problems
    [Details] [PDF] [Slides (PDF)] [Video]
    Prasoon Goyal
    October 2021. Ph.D. Proposal.
39. Incorporating Textual Resources to Improve Visual Question Answering
    [Details] [PDF] [Slides (PDF)]
    Jialin Wu
    September 2021. Ph.D. Proposal.
40. Supervised Attention from Natural Language Feedback for Reinforcement Learning
    [Details] [PDF]
    Clara Cecilia Cannon
    Masters Thesis, Department of Computer Science, The University of Texas at Austin, May 2021.
41. Copy That! Editing Sequences by Copying Spans
    [Details] [PDF] [Slides (PPT)] [Slides (PDF)] [Poster]
    Sheena Panthaplackel, Miltiadis Allamanis, Marc Brockschmidt
    In The AAAI Conference on Artificial Intelligence (AAAI), February 2021.
42. A Recap of Early Work onTheory and Knowledge Refinement
    [Details] [PDF] [Slides (PPT)]
    Raymond J. Mooney, Jude W. Shavlik
    In AAAI Spring Symposium on Combining Machine Learning and Knowledge Engineering, March 2021.
43. Deep Just-In-Time Inconsistency Detection Between Comments and Source Code
    [Details] [PDF] [Slides (PDF)] [Poster] [Video]
    Sheena Panthaplackel, Junyi Jessy Li, Milos Gligoric, Raymond J. Mooney
    In The AAAI Conference on Artificial Intelligence (AAAI), February 2021.
44. Improving VQA and its Explanations by Comparing Competing Explanations
    [Details] [PDF] [Slides (PDF)]
    Jialin Wu, Liyan Chen, Raymond J. Mooney
    In The AAAI Conference on Artificial Intelligence (AAAI), Explainable Agency in Artificial Intelligence Workshop, February 2021.
45. Dialog Policy Learning for Joint Clarification and Active Learning Queries
    [Details] [PDF] [Slides (PDF)] [Poster] [Video]
    Aishwarya Padmakumar, Raymond J. Mooney
    In The AAAI Conference on Artificial Intelligence (AAAI), February 2021.
46. Systematic Generalization on gSCAN with Language Conditioned Embedding
    [Details] [PDF] [Video]
    Tong Gao, Qi Huang and Raymond J. Mooney
    In The 1st Conference of the Asia-Pacific Chapter of the Association for Computational Linguistics and the 10th International Joint Conference on Natural Language Processing , December 2020.
47. Dialog as a Vehicle for Lifelong Learning of Grounded Language Understanding Systems
    [Details] [PDF] [Slides (PDF)]
    Aishwarya Padmakumar
    PhD Thesis, Department of Computer Science, The University of Texas at Austin, August 2020.
48. PixL2R: Guiding Reinforcement Learning using Natural Language by Mapping Pixels to Rewards
    [Details] [PDF]
    Prasoon Goyal, Scott Niekum, Raymond J. Mooney
    In 4th Conference on Robot Learning (CoRL), November 2020. Also presented on the 1st Language in Reinforcement Learning (LaReL) Workshop at ICML, July 2020 (Best Paper Award), the 6th Deep Reinforcement Learning Workshop at Neural Information Processing Systems (NeurIPS), Dec 2020.
49. Dialog as a Vehicle for Lifelong Learning
    [Details] [PDF] [Slides (PDF)] [Video]
    Aishwarya Padmakumar, Raymond J. Mooney
    In Position Paper Track at the SIGDIAL Special Session on Physically Situated Dialogue (RoboDial 2.0), July 2020.
50. Evaluating the Robustness of Natural Language Reward Shaping Models to Spatial Relations
    [Details] [PDF] [Slides (PPT)] [Slides (PDF)]
    Antony Yun
    May 2020. Undergraduate Honors Thesis, Computer Science Department, University of Texas at Austin.
51. Learning to Update Natural Language Comments Based on Code Changes
    [Details] [PDF] [Video]
    Sheena Panthaplackel, Pengyu Nie, Milos Gligoric, Junyi Jessy Li, and Raymond J. Mooney
    In Proceedings of the 58th Annual Conference of the Association for Computational Linguistics (ACL), July 2020.
52. Associating Natural Language Comment and Source Code Entities
    [Details] [PDF] [Slides (PDF)] [Poster]
    Sheena Panthaplackel, Milos Gligoric, Raymond J. Mooney and Junyi Jessy Li
    In The AAAI Conference on Artificial Intelligence (AAAI), February 2020.
53. Jointly Improving Parsing and Perception for Natural Language Commands through Human-Robot Dialog
    [Details] [PDF]
    Jesse Thomason, Aishwarya Padmakumar, Jivko Sinapov, Nick Walker, Yuqian Jiang, Harel Yedidsion, Justin Hart, Peter Stone, Raymond J. Mooney
    The Journal of Artificial Intelligence Research (JAIR), 67:327-374, February 2020.
54. Self-Critical Reasoning for Robust Visual Question Answering
    [Details] [PDF] [Slides (PDF)] [Poster]
    Jialin Wu and Raymond J. Mooney
    In Proceedings of Neural Information Processing Systems (NeurIPS) , December 2019.
55. Hidden State Guidance: Improving Image Captioning using An Image Conditioned Autoencoder
    [Details] [PDF] [Poster]
    Jialin Wu and Raymond J. Mooney
    In Proceedings of the Visually Grounded Interaction and Language Workshop at NeurIPS 2019, December 2019.
56. Optimal Use Of Verbal Instructions For Multi-Robot Human Navigation Guidance
    [Details] [PDF] [Slides (PDF)] [Video]
    Harel Yedidsion, Jacqueline Deans, Connor Sheehan, Mahathi Chillara, Justin Hart, Peter Stone, and Raymond J. Mooney
    In Proceedings of the Eleventh International Conference on Social Robotics, 133-143, 2019. Springer.
57. A Framework for Writing Trigger - Action Todo Comments in Executable Format
    [Details] [PDF] [Slides (PPT)]
    Pengyu Nie, Rishabh Rai, Junyi Jessy Li, Sarfraz Khurshid, Raymond J. Mooney, Milos Gligoric
    In Proceedings of the ACM Joint European Software Engineering Conference and Symposium on the Foundations of Software Engineering (ESEC/FSE), Tallinn, Estonia, August 2019. Distinguished Paper Award.
58. Using Natural Language for Reward Shaping in Reinforcement Learning
    [Details] [PDF] [Slides (PDF)] [Poster]
    Prasoon Goyal, Scott Niekum, Raymond J. Mooney
    In Proceedings of the 28th International Joint Conference on Artificial Intelligence, Macao, China, August 2019.
59. Generating Question Relevant Captions to Aid Visual Question Answering
    [Details] [PDF] [Slides (PPT)]
    Jialin Wu, Zeyuan Hu, Raymond J. Mooney
    In Proceedings of the 57th Annual Meeting of the Association for Computational Linguistics (ACL), Florence, Italy, August 2019.
60. Faithful Multimodal Explanation for Visual Question Answering
    [Details] [PDF] [Slides (PPT)]
    Jialin Wu and Raymond J. Mooney
    In Proceedings of the Second BlackboxNLP Workshop at ACL, 103-112, Florence, Italy, August 2019.
61. Do Human Rationales Improve Machine Explanations?
    [Details] [PDF] [Poster]
    Julia Strout, Ye Zhang, Raymond J. Mooney
    In Proceedings of the Second BlackboxNLP Workshop at ACL, 56-62, Florence, Italy, August 2019.
62. AInix: An open platform for natural language interfaces to shell commands
    [Details] [PDF]
    David Gros
    May 2019. Undergraduate Honors Thesis, Computer Science Department, University of Texas at Austin.
63. Improving Grounded Natural Language Understanding through Human-Robot Dialog
    [Details] [PDF]
    Jesse Thomason, Aishwarya Padmakumar, Jivko Sinapov, Nick Walker, Yuqian Jiang, Harel Yedidsion, Justin Hart, Peter Stone, and Raymond J. Mooney
    In IEEE International Conference on Robotics and Automation (ICRA), Montreal, Canada, May 2019.
64. Generating Animated Videos of Human Activities from Natural Language Descriptions
    [Details] [PDF] [Poster]
    Angela S. Lin, Lemeng Wu, Rodolfo Corona , Kevin Tai , Qixing Huang , Raymond J. Mooney
    In Proceedings of the Visually Grounded Interaction and Language Workshop at NeurIPS 2018, December 2018.
65. Learning a Policy for Opportunistic Active Learning
    [Details] [PDF]
    Aishwarya Padmakumar, Peter Stone, Raymond J. Mooney
    In Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing (EMNLP-18), Brussels, Belgium, November 2018.
66. Improved Models and Queries for Grounded Human-Robot Dialog
    [Details] [PDF]
    Aishwarya Padmakumar
    October 2018. PhD Proposal, Department of Computer Science, The University of Texas At Austin.
67. Interaction and Autonomy in RoboCup@Home and Building-Wide Intelligence
    [Details] [PDF]
    Justin Hart, Harel Yedidsion, Yuqian Jiang, Nick Walker, Rishi Shah, Jesse Thomason, Aishwarya Padmakumar, Rolando Fernandez, Jivko Sinapov, Raymond Mooney, Peter Stone
    In Artificial Intelligence (AI) for Human-Robot Interaction (HRI) symposium, AAAI Fall Symposium Series, Arlington, Virginia, October 2018.
68. Jointly Improving Parsing and Perception for Natural Language Commands through Human-Robot Dialog
    [Details] [PDF]
    Jesse Thomason, Aishwarya Padmakumar, Jivko Sinapov, Nick Walker, Yuqian Jiang, Harel Yedidsion, Justin Hart, Peter Stone, and Raymond J. Mooney
    In Late-breaking Track at the SIGDIAL Special Session on Physically Situated Dialogue (RoboDIAL-18), Melbourne, Australia, July 2018.
69. Explainable Improved Ensembling for Natural Language and Vision
    [Details] [PDF] [Slides (PPT)] [Slides (PDF)]
    Nazneen Rajani
    PhD Thesis, Department of Computer Science, The University of Texas at Austin, July 2018.
70. Jointly Improving Parsing and Perception for Natural Language Commands through Human-Robot Dialog
    [Details] [PDF]
    Jesse Thomason, Aishwarya Padmakumar, Jivko Sinapov, Nick Walker, Yuqian Jiang, Harel Yedidsion, Justin Hart, Peter Stone, and Raymond J. Mooney
    In RSS Workshop on Models and Representations for Natural Human-Robot Communication (MRHRC-18). Robotics: Science and Systems (RSS), June 2018.
71. Joint Image Captioning and Question Answering
    [Details] [PDF] [Poster]
    Jialin Wu, Zeyuan Hu and Raymond J. Mooney
    In VQA Challenge and Visual Dialog Workshop at the 31st IEEE Conference on Computer Vision and Pattern Recognition (CVPR-18) , June 2018.
72. Continually Improving Grounded Natural Language Understanding through Human-Robot Dialog
    [Details] [PDF]
    Jesse Thomason
    PhD Thesis, Department of Computer Science, The University of Texas at Austin, April 2018.
73. Stacking With Auxiliary Features for Visual Question Answering
    [Details] [PDF] [Poster]
    Nazneen Fatema Rajani, Raymond J. Mooney
    In Proceedings of the 16th Annual Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, 2217-2226, 2018.
74. Natural Language Processing and Program Analysis for Supporting Todo Comments as Software Evolves
    [Details] [PDF]
    Pengyu Nie, Junyi Jessy Li, Sarfraz Khurshid, Raymond Mooney, Milos Gligoric
    In In Proceedings of the AAAI Workshop on NLP for Software Engineering, February 2018.
75. Guiding Exploratory Behaviors for Multi-Modal Grounding of Linguistic Descriptions
    [Details] [PDF]
    Jesse Thomason, Jivko Sinapov, Raymond Mooney, Peter Stone
    In Proceedings of the Thirty-Second AAAI Conference on Artificial Intelligence (AAAI-18) , February 2018.
76. Multi-modal Predicate Identification using Dynamically Learned Robot Controllers
    [Details] [PDF]
    Saeid Amiri and Suhua Wei and Shiqi Zhang and Jivko Sinapov and Jesse Thomason and Peter Stone
    In Proceedings of the 27th International Joint Conference on Artificial Intelligence (IJCAI-18), Stockholm, Sweden, July 2018.
77. Ensembling Visual Explanations for VQA
    [Details] [PDF] [Poster]
    Nazneen Fatema Rajani, Raymond J. Mooney
    In Proceedings of the NIPS 2017 workshop on Visually-Grounded Interaction and Language (ViGIL), December 2017.
78. Distributional modeling on a diet: One-shot word learning from text only
    [Details] [PDF]
    Su Wang and Stephen Roller and Katrin Erk
    In In Proceedings of the 8th International Joint Conference on Natural Language Processing (IJCNLP-17), Taipei, Taiwan, November 2017.
79. Dialog for Language to Code
    [Details] [PDF] [Poster]
    Shobhit Chaurasia and Raymond J. Mooney
    In Proceedings of the 8th International Joint Conference on Natural Language Processing (IJCNLP-17), 175-180, Taipei, Taiwan, November 2017.
80. Leveraging Discourse Information Effectively for Authorship Attribution
    [Details] [PDF] [Slides (PDF)] [Video]
    Elisa Ferracane and Su Wang and Raymond J. Mooney
    In In Proceedings of the 8th International Joint Conference on Natural Language Processing (IJCNLP-17), 584–593, Taipei, Taiwan, November 2017.
81. Improving Black-box Speech Recognition using Semantic Parsing
    [Details] [PDF] [Poster]
    Rodolfo Corona and Jesse Thomason and Raymond J. Mooney
    In Proceedings of the 8th International Joint Conference on Natural Language Processing (IJCNLP-17), 122-127, Taipei, Taiwan, November 2017.
82. Opportunistic Active Learning for Grounding Natural Language Descriptions
    [Details] [PDF]
    Jesse Thomason and Aishwarya Padmakumar and Jivko Sinapov and Justin Hart and Peter Stone and Raymond J. Mooney
    In Sergey Levine and Vincent Vanhoucke and Ken Goldberg, editors, Proceedings of the 1st Annual Conference on Robot Learning (CoRL-17), 67--76, Mountain View, California, November 2017. PMLR.
83. Natural-Language Video Description with Deep Recurrent Neural Networks
    [Details] [PDF] [Slides (PDF)]
    Subhashini Venugopalan
    PhD Thesis, Department of Computer Science, The University of Texas at Austin, August 2017.
84. Advances in Statistical Script Learning
    [Details] [PDF] [Slides (PPT)]
    Karl Pichotta
    PhD Thesis, Department of Computer Science, The University of Texas at Austin, August 2017.
85. Dialog for Natural Language to Code
    [Details] [PDF]
    Shobhit Chaurasia
    2017. Masters Thesis, Computer Science Department, University of Texas at Austin.
86. Using Explanations to Improve Ensembling of Visual Question Answering Systems
    [Details] [PDF] [Poster]
    Nazneen Fatema Rajani and Raymond J. Mooney
    In Proceedings of the IJCAI 2017 Workshop on Explainable Artificial Intelligence (XAI), 43-47, Melbourne, Australia, August 2017.
87. Guiding Interaction Behaviors for Multi-modal Grounded Language Learning
    [Details] [PDF]
    Jesse Thomason and Jivko Sinapov and Raymond J. Mooney
    In Proceedings of the Workshop on Language Grounding for Robotics at ACL 2017 (RoboNLP-17), Vancouver, Canada, August 2017.
88. Multi-Modal Word Synset Induction
    [Details] [PDF]
    Jesse Thomason and Raymond J. Mooney
    In Proceedings of the 26th International Joint Conference on Artificial Intelligence (IJCAI-17), 4116--4122, Melbourne, Australia, 2017.
89. Stacking With Auxiliary Features
    [Details] [PDF] [Slides (PDF)] [Poster]
    Nazneen Fatema Rajani and Raymond J. Mooney
    In Proceedings of the 26th International Joint Conference on Artificial Intelligence (IJCAI-17), 2634-2640, Melbourne, Australia, 2017.
90. Integrated Learning of Dialog Strategies and Semantic Parsing
    [Details] [PDF]
    Aishwarya Padmakumar and Jesse Thomason and Raymond J. Mooney
    In Proceedings of the 15th Conference of the European Chapter of the Association for Computational Linguistics (EACL 2017), 547--557, Valencia, Spain, April 2017.
91. Captioning Images with Diverse Objects
    [Details] [PDF] [Slides (PDF)] [Poster]
    Subhashini Venugopalan and Lisa Anne Hendricks and Marcus Rohrbach and Raymond Mooney and Trevor Darrell and Kate Saenko
    In Proceedings of the 30th IEEE Conference on Computer Vision and Pattern Recognition (CVPR-17), 5753--5761, 2017.
92. BWIBots: A platform for bridging the gap between AI and human--robot interaction research
    [Details] [PDF]
    Piyush Khandelwal and Shiqi Zhang and Jivko Sinapov and Matteo Leonetti and Jesse Thomason and Fangkai Yang and Ilaria Gori and Maxwell Svetlik and Priyanka Khante and Vladimir Lifschitz and J. K. Aggarwal and Raymond Mooney and Peter Stone
    The International Journal of Robotics Research, 2017.
93. Stacking With Auxiliary Features for Combining Supervised and Unsupervised Ensembles
    [Details] [PDF]
    Nazneen Fatema Rajani and Raymond J. Mooney
    In Proceedings of the Ninth Text Analysis Conference (TAC 2016), 2016.
94. Stacking With Auxiliary Features: Improved Ensembling for Natural Language and Vision
    [Details] [PDF] [Slides (PDF)]
    Nazneen Fatema Rajani
    November 2016. PhD proposal, Department of Computer Science, The University of Texas at Austin.
95. An Analysis of Using Semantic Parsing for Speech Recognition
    [Details] [PDF] [Slides (PPT)]
    Rodolfo Corona
    2016. Undergraduate Honors Thesis, Computer Science Department, University of Texas at Austin.
96. Continuously Improving Natural Language Understanding for Robotic Systems through Semantic Parsing, Dialog, and Multi-modal Perception
    [Details] [PDF]
    Jesse Thomason
    November 2016. PhD proposal, Department of Computer Science, The University of Texas at Austin.
97. Natural Language Semantics Using Probabilistic Logic
    [Details] [PDF] [Slides (PPT)] [Slides (PDF)]
    I. Beltagy
    PhD Thesis, Department of Computer Science, The University of Texas at Austin, December 2016.
98. Statistical Script Learning with Recurrent Neural Networks
    [Details] [PDF] [Poster]
    Karl Pichotta and Raymond J. Mooney
    In Proceedings of the Workshop on Uphill Battles in Language Processing (UBLP) at EMNLP 2016, Austin, TX, November 2016.
99. PIC a Different Word: A Simple Model for Lexical Substitution in Context
    [Details] [PDF]
    Stephen Roller and Katrin Erk
    In Proceedings of the 15th Annual Conference of the North American Chapter of the Association for Computational Linguistics (NAACL-16), 1121-1126, San Diego, California, 2016.
100. MGNC-CNN: A Simple Approach to Exploiting Multiple Word Embeddings for Sentence Classification
     [Details] [PDF]
     Ye Zhang and Stephen Roller and Byron Wallace.
     In Proceedings of the 15th Annual Conference of the North American Chapter of the Association for Computational Linguistics (NAACL-16), 1522--1527, San Diego, California, 2016.
101. Stacking With Auxiliary Features
     [Details] [PDF]
     Nazneen Fatema Rajani and Raymond J. Mooney
     ArXiv preprint arXiv:1605.08764, 2016.
102. Improved Semantic Parsers For If-Then Statements
     [Details] [PDF]
     I. Beltagy and Chris Quirk
     To Appear In Proceedings of the 54th Annual Meeting of the Association for Computational Linguistics (ACL-16), Berlin, Germany, 2016.
103. Combining Supervised and Unsupervised Ensembles for Knowledge Base Population
     [Details] [PDF]
     Nazneen Fatema Rajani and Raymond J. Mooney
     To Appear In Proceedings of the 2016 Conference on Empirical Methods in Natural Language Processing (EMNLP-16), 2016.
104. Using Sentence-Level LSTM Language Models for Script Inference
     [Details] [PDF] [Slides (PPT)] [Slides (PDF)]
     Karl Pichotta and Raymond J. Mooney
     In Proceedings of the 54th Annual Meeting of the Association for Computational Linguistics (ACL-16), 279--289, Berlin, Germany, 2016.
105. Learning Multi-Modal Grounded Linguistic Semantics by Playing "I Spy"
     [Details] [PDF]
     Jesse Thomason and Jivko Sinapov and Maxwell Svetlik and Peter Stone and Raymond J. Mooney
     In Proceedings of the 25th International Joint Conference on Artificial Intelligence (IJCAI-16), 3477--3483, New York City, 2016.
106. Improving LSTM-based Video Description with Linguistic Knowledge Mined from Text
     [Details] [PDF] [Poster]
     Subhashini Venugopalan and Lisa Anne Hendricks and Raymond Mooney and Kate Saenko
     In Proceedings of the 2016 Conference on Empirical Methods in Natural Language Processing (EMNLP-16), 1961--1966, Austin, Texas, 2016.
107. Deep Compositional Captioning: Describing Novel Object Categories without Paired Training Data
     [Details] [PDF]
     Lisa Anne Hendricks and Subhashini Venugopalan and Marcus Rohrbach and Raymond Mooney and Kate Saenko and Trevor Darrell
     In Proceedings of the 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR-16), 1--10, 2016.
108. Learning Statistical Scripts with LSTM Recurrent Neural Networks
     [Details] [PDF] [Slides (PPT)] [Slides (PDF)]
     Karl Pichotta and Raymond J. Mooney
     In Proceedings of the 30th AAAI Conference on Artificial Intelligence (AAAI-16), Phoenix, Arizona, February 2016.
109. Representing Meaning with a Combination of Logical and Distributional Models
     [Details] [PDF]
     I. Beltagy and Stephen Roller and Pengxiang Cheng and Katrin Erk and Raymond J. Mooney
     The special issue of Computational Linguistics on Formal Distributional Semantics, 42(4), 2016.
110. Stacked Ensembles of Information Extractors for Knowledge-Base Population by Combining Supervised and Unsupervised Approaches
     [Details] [PDF] [Slides (PDF)]
     Nazneen Fatema Rajani and Raymond J Mooney
     In Proceedings of the Eighth Text Analysis Conference (TAC 2015), November 2015.
111. Statistical Script Learning with Recurrent Neural Nets
     [Details] [PDF] [Slides (PDF)]
     Karl Pichotta
     December 2015. PhD proposal, Department of Computer Science, The University of Texas at Austin.
112. Natural Language Video Description using Deep Recurrent Neural Networks
     [Details] [PDF] [Slides (PDF)]
     Subhashini Venugopalan
     November 2015. PhD proposal, Department of Computer Science, The University of Texas at Austin.
113. Knowledge Transfer Using Latent Variable Models
     [Details] [PDF] [Slides (PDF)]
     Ayan Acharya
     PhD Thesis, Department of Electrical and Computer Engineering, The University of Texas at Austin, August 2015.
114. Inducing Grammars from Linguistic Universals and Realistic Amounts of Supervision
     [Details] [PDF]
     Dan Garrette
     PhD Thesis, Department of Computer Science, The University of Texas at Austin, 2015.
115. A Supertag-Context Model for Weakly-Supervised CCG Parser Learning
     [Details] [PDF] [Slides (PDF)]
     Dan Garrette and Chris Dyer and Jason Baldridge and Noah A. Smith
     In Proceedings of the 2015 Conference on Computational Natural Language Learning (CoNLL-2015), 22--31, Beijing, China, 2015.
116. Sequence to Sequence -- Video to Text
     [Details] [PDF]
     Subhashini Venugopalan and Marcus Rohrbach and Jeff Donahue and Raymond J. Mooney and Trevor Darrell and Kate Saenko
     In Proceedings of the 2015 International Conference on Computer Vision (ICCV-15), Santiago, Chile, December 2015.
117. Stacked Ensembles of Information Extractors for Knowledge-Base Population
     [Details] [PDF] [Slides (PPT)]
     Vidhoon Viswanathan and Nazneen Fatema Rajani and Yinon Bentor and Raymond J. Mooney
     In Proceedings of the 53rd Annual Meeting of the Association for Computational Linguistics (ACL-15), 177-187, Beijing, China, July 2015.
118. Language to Code: Learning Semantic Parsers for If-This-Then-That Recipes
     [Details] [PDF] [Poster]
     Chris Quirk and Raymond Mooney and Michel Galley
     In Proceedings of the 53rd Annual Meeting of the Association for Computational Linguistics (ACL-15), 878--888, Beijing, China, July 2015.
119. Knowledge Base Population using Stacked Ensembles of Information Extractors
     [Details] [PDF]
     Vidhoon Viswanathan
     Masters Thesis, Department of Computer Science, The University of Texas at Austin, May 2015.
120. Learning to Interpret Natural Language Commands through Human-Robot Dialog
     [Details] [PDF]
     Jesse Thomason and Shiqi Zhang and Raymond Mooney and Peter Stone
     In Proceedings of the 2015 International Joint Conference on Artificial Intelligence (IJCAI), 1923--1929, Buenos Aires, Argentina, July 2015.
121. Translating Videos to Natural Language Using Deep Recurrent Neural Networks
     [Details] [PDF] [Slides (PDF)]
     Subhashini Venugopalan and Huijuan Xu and Jeff Donahue and Marcus Rohrbach and Raymond Mooney and Kate Saenko
     In Proceedings the 2015 Conference of the North American Chapter of the Association for Computational Linguistics -- Human Language Technologies (NAACL HLT 2015), 1494--1504, Denver, Colorado, June 2015.
122. Unsupervised Code-Switching for Multilingual Historical Document Transcription
     [Details] [PDF] [Slides (PDF)]
     Dan Garrette and Hannah Alpert-Abrams and Taylor Berg-Kirkpatrick and Dan Klein
     In Proceedings the 2015 Conference of the North American Chapter of the Association for Computational Linguistics -- Human Language Technologies (NAACL HLT 2015), 1036--1041, Denver, Colorado, June 2015.
123. On the Proper Treatment of Quantifiers in Probabilistic Logic Semantics
     [Details] [PDF] [Slides (PPT)]
     I. Beltagy and Katrin Erk
     In Proceedings of the 11th International Conference on Computational Semantics (IWCS-2015), London, UK, April 2015.
124. Weakly-Supervised Grammar-Informed Bayesian CCG Parser Learning
     [Details] [PDF] [Slides (PDF)]
     Dan Garrette, Chris Dyer, Jason Baldridge, Noah A. Smith
     In Proceedings of the Twenty-Ninth AAAI Conference on Artificial Intelligence (AAAI-15), Austin, TX, January 2015.
125. University of Texas at Austin KBP 2014 Slot Filling System: Bayesian Logic Programs for Textual Inference
     [Details] [PDF]
     Yinon Bentor and Vidhoon Viswanathan and Raymond Mooney
     In Proceedings of the Seventh Text Analysis Conference: Knowledge Base Population (TAC 2014), 2014.
126. Natural Language Semantics using Probabilistic Logic
     [Details] [PDF] [Slides (PPT)]
     I. Beltagy
     October 2014. PhD proposal, Department of Computer Science, The University of Texas at Austin.
127. Weakly-Supervised Bayesian Learning of a CCG Supertagger
     [Details] [PDF] [Slides (PDF)] [Poster]
     Dan Garrette and Chris Dyer and Jason Baldridge and Noah A. Smith
     In Proceedings of the Eighteenth Conference on Computational Natural Language Learning (CoNLL-2014), 141--150, Baltimore, MD, June 2014.
128. Inclusive yet Selective: Supervised Distributional Hypernymy Detection
     [Details] [PDF]
     Stephen Roller and Katrin Erk and Gemma Boleda
     In Proceedings of the 25th International Conference on Computational Linguistics (COLING 2014), 1025--1036, Dublin, Ireland, August 2014.
129. UTexas: Natural Language Semantics using Distributional Semantics and Probabilistic Logic
     [Details] [PDF]
     I. Beltagy and Stephen Roller and Gemma Boleda and and Katrin Erk and Raymond J. Mooney
     In The 8th Workshop on Semantic Evaluation (SemEval-2014), 796--801, Dublin, Ireland, August 2014.
130. Integrating Language and Vision to Generate Natural Language Descriptions of Videos in the Wild
     [Details] [PDF]
     Jesse Thomason and Subhashini Venugopalan and Sergio Guadarrama and Kate Saenko and Raymond Mooney
     In Proceedings of the 25th International Conference on Computational Linguistics (COLING 2014), 1218--1227, Dublin, Ireland, August 2014.
131. Efficient Markov Logic Inference for Natural Language Semantics
     [Details] [PDF] [Poster]
     I. Beltagy and Raymond J. Mooney
     In Proceedings of the Fourth International Workshop on Statistical Relational AI at AAAI (StarAI-2014), 9--14, Quebec City, Canada, July 2014.
132. Integrating Visual and Linguistic Information to Describe Properties of Objects
     [Details] [PDF]
     Calvin MacKenzie
     2014. Undergraduate Honors Thesis, Computer Science Department, University of Texas at Austin.
133. Semantic Parsing using Distributional Semantics and Probabilistic Logic
     [Details] [PDF] [Poster]
     I. Beltagy and Katrin Erk and Raymond Mooney
     In Proceedings of ACL 2014 Workshop on Semantic Parsing (SP-2014), 7--11, Baltimore, MD, June 2014.
134. Probabilistic Soft Logic for Semantic Textual Similarity
     [Details] [PDF] [Poster]
     I. Beltagy and Katrin Erk and Raymond J. Mooney
     In Proceedings of the 52nd Annual Meeting of the Association for Computational Linguistics (ACL-14), 1210--1219, Baltimore, MD, 2014.
135. Plan Recognition Using Statistical Relational Models
     [Details] [PDF]
     Sindhu Raghavan and Parag Singla and Raymond J. Mooney
     In Sukthankar, G. and Geib, C. and Bui, H.H. and Pynadath, D. and Goldman, R.P., editors, Plan, Activity, and Intent Recognition: Theory and Practice, 57--85, Burlington, MA, 2014. Morgan Kaufmann.
136. Active Multitask Learning Using Both Latent and Supervised Shared Topics
     [Details] [PDF] [Slides (PDF)]
     Ayan Acharya and Raymond J. Mooney and Joydeep Ghosh
     In Proceedings of the 2014 SIAM International Conference on Data Mining (SDM14), Philadelphia, Pennsylvania, April 2014.
137. Statistical Script Learning with Multi-Argument Events
     [Details] [PDF] [Poster]
     Karl Pichotta and Raymond J. Mooney
     In Proceedings of the 14th Conference of the European Chapter of the Association for Computational Linguistics (EACL 2014), 220--229, Gothenburg, Sweden, April 2014.
138. University of Texas at Austin KBP 2013 Slot Filling System: Bayesian Logic Programs for Textual Inference
     [Details] [PDF]
     Yinon Bentor and Amelia Harrison and Shruti Bhosale and Raymond Mooney
     In Proceedings of the Sixth Text Analysis Conference (TAC 2013), 2013.
139. YouTube2Text: Recognizing and Describing Arbitrary Activities Using Semantic Hierarchies and Zero-shot Recognition
     [Details] [PDF] [Poster]
     Sergio Guadarrama, Niveda Krishnamoorthy, Girish Malkarnenkar, Subhashini Venugopalan, Raymond Mooney, Trevor Darrell, Kate Saenko
     In Proceedings of the 14th International Conference on Computer Vision (ICCV-2013), 2712--2719, Sydney, Australia, December 2013.
140. A Multimodal LDA Model Integrating Textual, Cognitive and Visual Modalities
     [Details] [PDF]
     Stephen Roller and Sabine Schulte im Walde
     In Proceedings of the 2013 Conference on Empirical Methods in Natural Language Processing (EMNLP 2013), 1146--1157, Seattle, WA, October 2013.
141. Identifying Phrasal Verbs Using Many Bilingual Corpora
     [Details] [PDF] [Poster]
     Karl Pichotta and John DeNero
     In Proceedings of the 2013 Conference on Empirical Methods in Natural Language Processing (EMNLP 2013), 636--646, Seattle, WA, October 2013.
142. Detecting Promotional Content in Wikipedia
     [Details] [PDF] [Slides (PPT)]
     Shruti Bhosale and Heath Vinicombe and Raymond J. Mooney
     In Proceedings of the 2013 Conference on Empirical Methods in Natural Language Processing (EMNLP 2013), 1851--1857, Seattle, WA, October 2013.
143. Grounded Language Learning Models for Ambiguous Supervision
     [Details] [PDF] [Slides (PPT)]
     Joo Hyun Kim
     PhD Thesis, Department of Computer Science, University of Texas at Austin, December 2013.
144. Generating Natural-Language Video Descriptions Using Text-Mined Knowledge
     [Details] [PDF] [Slides (PPT)]
     Niveda Krishnamoorthy, Girish Malkarnenkar, Raymond J. Mooney, Kate Saenko, Sergio Guadarrama
     In Proceedings of the NAACL HLT Workshop on Vision and Language (WVL '13), 10--19, Atlanta, Georgia, July 2013.
145. Using Both Latent and Supervised Shared Topics for Multitask Learning
     [Details] [PDF] [Slides (PDF)]
     Ayan Acharya, Aditya Rawal, Raymond J. Mooney, Eduardo R. Hruschka
     In Proceedings of the European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML/PKDD), 369--384, Prague, Czech Republic, September 2013.
146. Real-World Semi-Supervised Learning of POS-Taggers for Low-Resource Languages
     [Details] [PDF]
     Dan Garrette and Jason Mielens and Jason Baldridge
     In Proceedings of the 51st Annual Meeting of the Association for Computational Linguistics (ACL-2013), 583--592, Sofia, Bulgaria, August 2013.
147. Online Inference-Rule Learning from Natural-Language Extractions
     [Details] [PDF] [Poster]
     Sindhu Raghavan and Raymond J. Mooney
     In Proceedings of the 3rd Statistical Relational AI (StaRAI-13) workshop at AAAI '13, July 2013.
148. Adapting Discriminative Reranking to Grounded Language Learning
     [Details] [PDF] [Slides (PPT)]
     Joohyun Kim and Raymond J. Mooney
     In Proceedings of the 51st Annual Meeting of the Association for Computational Linguistics (ACL-2013), 218--227, Sofia, Bulgaria, August 2013.
149. Montague Meets Markov: Deep Semantics with Probabilistic Logical Form
     [Details] [PDF] [Slides (PPT)]
     I. Beltagy, Cuong Chau, Gemma Boleda, Dan Garrette, Katrin Erk, Raymond Mooney
     In Proceedings of the Second Joint Conference on Lexical and Computational Semantics (*Sem-2013), 11--21, Atlanta, GA, June 2013.
150. A Formal Approach to Linking Logical Form and Vector-Space Lexical Semantics
     [Details] [PDF]
     Dan Garrette, Katrin Erk, Raymond J. Mooney
     In Harry Bunt, Johan Bos, and Stephen Pulman, editors, Computing Meaning, 27--48, Berlin, 2013. Springer.
151. Learning a Part-of-Speech Tagger from Two Hours of Annotation
     [Details] [PDF] [Slides (PDF)] [Video]
     Dan Garrette, Jason Baldridge
     In Proceedings of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies (NAACL-HLT-13), 138--147, Atlanta, GA, June 2013.
152. Generating Natural-Language Video Descriptions Using Text-Mined Knowledge
     [Details] [PDF] [Slides (PPT)]
     Niveda Krishnamoorthy, Girish Malkarnenkar, Raymond J. Mooney, Kate Saenko, Sergio Guadarrama
     In Proceedings of the 27th AAAI Conference on Artificial Intelligence (AAAI-2013), 541--547, July 2013.
153. Latent Variable Models of Distributional Lexical Semantics
     [Details] [PDF]
     Joseph Reisinger
     PhD Thesis, Department of Computer Science, University of Texas at Austin, May 2012.
154. Review Quality Aware Collaborative Filtering
     [Details] [PDF]
     Sindhu Raghavan and Suriya Ganasekar and Joydeep Ghosh
     In Sixth ACM Conference on Recommender Systems (RecSys 2012), 123--130, September 2012.
155. Bayesian Logic Programs for Plan Recognition and Machine Reading
     [Details] [PDF] [Slides (PPT)]
     Sindhu Raghavan
     PhD Thesis, Department of Computer Science, University of Texas at Austin, December 2012. 170.
156. Type-Supervised Hidden Markov Models for Part-of-Speech Tagging with Incomplete Tag Dictionaries
     [Details] [PDF]
     Dan Garrette and Jason Baldridge
     In Proceedings of the Conference on Empirical Methods in Natural Language Processing and Computational Natural Language Learning (EMNLP-CoNLL 2012), 821--831, Jeju, Korea, July 2012.
157. Improving Video Activity Recognition using Object Recognition and Text Mining
     [Details] [PDF] [Slides (PPT)]
     Tanvi S. Motwani and Raymond J. Mooney
     In Proceedings of the 20th European Conference on Artificial Intelligence (ECAI-2012), 600--605, August 2012.
158. Generative Models of Grounded Language Learning with Ambiguous Supervision
     [Details] [PDF] [Slides (PPT)]
     Joohyun Kim
     Technical Report, PhD proposal, Department of Computer Science, The University of Texas at Austin, June 2012.
159. Unsupervised PCFG Induction for Grounded Language Learning with Highly Ambiguous Supervision
     [Details] [PDF]
     Joohyun Kim and Raymond J. Mooney
     In Proceedings of the Conference on Empirical Methods in Natural Language Processing and Natural Language Learning (EMNLP-CoNLL '12), 433--444, Jeju Island, Korea, July 2012.
160. Fast Online Lexicon Learning for Grounded Language Acquisition
     [Details] [PDF] [Slides (PPT)]
     David L. Chen
     In Proceedings of the 50th Annual Meeting of the Association for Computational Linguistics (ACL-2012), 430--439, July 2012.
161. Learning to "Read Between the Lines" using Bayesian Logic Programs
     [Details] [PDF] [Slides (PPT)]
     Sindhu Raghavan and Raymond J. Mooney and Hyeonseo Ku
     In Proceedings of the 50th Annual Meeting of the Association for Computational Linguistics (ACL-2012), 349--358, July 2012.
162. Learning Language from Ambiguous Perceptual Context
     [Details] [PDF] [Slides (PPT)]
     David L. Chen
     PhD Thesis, Department of Computer Science, University of Texas at Austin, May 2012. 196.
163. Constraint Propagation for Efficient Inference in Markov Logic
     [Details] [PDF] [Slides (PDF)]
     Tivadar Papai, Parag Singla and Henry Kautz
     In Proceedings of 17th International Conference on Principles and Practice of Constraint Programming (CP 2011), Lecture Notes in Computer Science (LNCS), 691-705, September 2011.
164. Online Structure Learning for Markov Logic Networks
     [Details] [PDF] [Slides (PPT)]
     Tuyen N. Huynh and Raymond J. Mooney
     In Proceedings of the European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML-PKDD 2011), 81-96, September 2011.
165. Abductive Plan Recognition by Extending Bayesian Logic Programs
     [Details] [PDF] [Slides (PPT)]
     Sindhu Raghavan, Raymond J. Mooney
     In Proceedings of the European Conference on Machine Learning/Principles and Practice of Knowledge Discovery in Databases (ECML-PKDD 2011), 629-644, September 2011.
166. Building a Persistent Workforce on Mechanical Turk for Multilingual Data Collection
     [Details] [PDF] [Slides (PPT)]
     David L. Chen and William B. Dolan
     In Proceedings of The 3rd Human Computation Workshop (HCOMP 2011), August 2011.
167. Learning to Interpret Natural Language Navigation Instructions from Observations
     [Details] [PDF] [Slides (PPT)]
     David L. Chen and Raymond J. Mooney
     In Proceedings of the 25th AAAI Conference on Artificial Intelligence (AAAI-2011), 859-865, August 2011.
168. Abductive Markov Logic for Plan Recognition
     [Details] [PDF] [Slides (PPT)]
     Parag Singla and Raymond J. Mooney
     In Proceedings of the 25th AAAI Conference on Artificial Intelligence (AAAI-2011), 1069-1075, August 2011.
169. Cross-Cutting Models of Lexical Semantics
     [Details] [PDF] [Slides (PDF)]
     Joseph Reisinger and Raymond Mooney
     In Proceedings of The Conference on Empirical Methods in Natural Language Processing (EMNLP 2011), 1405-1415, July 2011.
170. Panning for Gold: Finding Relevant Semantic Content for Grounded Language Learning
     [Details] [PDF] [Slides (PDF)]
     David L. Chen and Raymond J. Mooney
     In Proceedings of Symposium on Machine Learning in Speech and Language Processing (MLSLP 2011), June 2011.
171. Fine-Grained Class Label Markup of Search Queries
     [Details] [PDF]
     Joseph Reisinger and Marius Pasca
     In Proceedings of The 49th Annual Meeting of the Association for Computational Linguistics: Human Language Technologies (ACL-HLT 2011), 1200-1209, June 2011.
172. Collecting Highly Parallel Data for Paraphrase Evaluation
     [Details] [PDF] [Slides (PPT)]
     David L. Chen and William B. Dolan
     In Proceedings of the 49th Annual Meeting of the Association for Computational Linguistics, 190-200, Portland, Oregon, USA, June 2011.
173. Extending Bayesian Logic Programs for Plan Recognition and Machine Reading
     [Details] [PDF] [Slides (PPT)]
     Sindhu V. Raghavan
     Technical Report, PhD proposal, Department of Computer Science, The University of Texas at Austin, May 2011.
174. Improving the Accuracy and Scalability of Discriminative Learning Methods for Markov Logic Networks
     [Details] [PDF] [Slides (PPT)]
     Tuyen N. Huynh
     PhD Thesis, Department of Computer Science, University of Texas at Austin, May 2011.
     159 pages.
175. Online Max-Margin Weight Learning for Markov Logic Networks
     [Details] [PDF] [Slides (PPT)]
     Tuyen N. Huynh and Raymond J. Mooney
     In Proceedings of the Eleventh SIAM International Conference on Data Mining (SDM11), 642--651, Mesa, Arizona, USA, April 2011.
176. Implementing Weighted Abduction in Markov Logic
     [Details] [PDF]
     James Blythe, Jerry R. Hobbs, Pedro Domingos, Rohit J. Kate, Raymond J. Mooney
     In Proceedings of the International Conference on Computational Semantics, 55--64, Oxford, England, January 2011.
177. Integrating Logical Representations with Probabilistic Information using Markov Logic
     [Details] [PDF] [Slides (PDF)]
     Dan Garrette, Katrin Erk, Raymond Mooney
     In Proceedings of the International Conference on Computational Semantics, 105--114, Oxford, England, January 2011.
178. A Mixture Model with Sharing for Lexical Semantics
     [Details] [PDF] [Slides (PDF)]
     Joseph Reisinger and Raymond J. Mooney
     In Proceedings of the Conference on Empirical Methods in Natural Language Processing (EMNLP-2010), 1173--1182, MIT, Massachusetts, USA, October 9--11 2010.
179. Generative Alignment and Semantic Parsing for Learning from Ambiguous Supervision
     [Details] [PDF]
     Joohyun Kim and Raymond J. Mooney
     In Proceedings of the 23rd International Conference on Computational Linguistics (COLING 2010), 543--551, Beijing, China, August 2010.
180. Learning to Predict Readability using Diverse Linguistic Features
     [Details] [PDF] [Slides (PPT)]
     Rohit J. Kate, Xiaoqiang Luo, Siddharth Patwardhan, Martin Franz, Radu Florian, Raymond J. Mooney, Salim Roukos and Chris Welty
     In 23rd International Conference on Computational Linguistics (COLING 2010), 2010.
181. Cross-cutting Models of Distributional Lexical Semantics
     [Details] [PDF] [Slides (PDF)]
     Joseph S. Reisinger
     June 2010. Ph.D. proposal, Department of Computer Sciences, University of Texas at Austin.
182. Spherical Topic Models
     [Details] [PDF] [Slides (PDF)]
     Joseph Reisinger, Austin Waters, Bryan Silverthorn, and Raymond J. Mooney
     In Proceedings of the 27th International Conference on Machine Learning (ICML 2010), 2010.
183. Joint Entity and Relation Extraction using Card-Pyramid Parsing
     [Details] [PDF] [Slides (PPT)]
     Rohit J. Kate and Raymond J. Mooney
     In Proceedings of the Fourteenth Conference on Computational Natural Language Learning (CoNLL-2010), 203--212, Uppsala, Sweden, July 2010.
184. Learning for Semantic Parsing Using Statistical Syntactic Parsing Techniques
     [Details] [PDF] [Slides (PPT)]
     Ruifang Ge
     PhD Thesis, Department of Computer Science, University of Texas at Austin, Austin, TX, May 2010. 165 pages.
185. Online Max-Margin Weight Learning with Markov Logic Networks
     [Details] [PDF] [Slides (PPT)]
     Tuyen N. Huynh and Raymond J. Mooney
     In Proceedings of the AAAI-10 Workshop on Statistical Relational AI (Star-AI 10), 32--37, Atlanta, GA, July 2010.
186. Bayesian Abductive Logic Programs
     [Details] [PDF] [Slides (PPT)]
     Sindhu Raghavan and Raymond Mooney
     In Proceedings of the AAAI-10 Workshop on Statistical Relational AI (Star-AI 10), 82--87, Atlanta, GA, July 2010.
187. Authorship Attribution Using Probabilistic Context-Free Grammars
     [Details] [PDF] [Slides (PPT)]
     Sindhu Raghavan, Adriana Kovashka and Raymond Mooney
     In Proceedings of the 48th Annual Meeting of the Association for Computational Linguistics (ACL-2010), 38--42, 2010.
188. Using Closed Captions as Supervision for Video Activity Recognition
     [Details] [PDF]
     Sonal Gupta, Raymond J. Mooney
     In Proceedings of the Twenty-Fourth AAAI Conference on Artificial Intelligence (AAAI-2010), 1083--1088, Atlanta, GA, July 2010.
189. Multi-Prototype Vector-Space Models of Word Meaning
     [Details] [PDF] [Slides (PDF)]
     Joseph Reisinger, Raymond J. Mooney
     In Proceedings of the 11th Annual Conference of the North American Chapter of the Association for Computational Linguistics (NAACL-2010), 109-117, 2010.
190. Training a Multilingual Sportscaster: Using Perceptual Context to Learn Language
     [Details] [PDF]
     David L. Chen, Joohyun Kim, Raymond J. Mooney
     Journal of Artificial Intelligence Research, 37:397--435, 2010.
191. Learning Language from Perceptual Context
     [Details] [PDF] [Slides (PPT)]
     David L. Chen
     December 2009. Ph.D. proposal, Department of Computer Sciences, University of Texas at Austin.
192. Discriminative Learning with Markov Logic Networks
     [Details] [PDF] [Slides (PPT)]
     Tuyen N. Huynh
     October 2009. Ph.D. proposal, Department of Computer Sciences, University of Texas at Austin.
193. Spherical Topic Models
     [Details] [PDF]
     Joseph Reisinger, Austin Waters, Bryan Silverthorn, and Raymond Mooney
     In NIPS'09 workshop: Applications for Topic Models: Text and Beyond, 2009.
194. Activity Retrieval in Closed Captioned Videos
     [Details] [PDF]
     Sonal Gupta
     Masters Thesis, Department of Computer Sciences, University of Texas at Austin, August 2009. 64 pages.
195. Learning with Markov Logic Networks: Transfer Learning, Structure Learning, and an Application to Web Query Disambiguation
     [Details] [PDF]
     Lilyana Mihalkova
     PhD Thesis, Department of Computer Sciences, University of Texas at Austin, Austin, TX, August 2009. 176 pages.
196. Max-Margin Weight Learning for Markov Logic Networks
     [Details] [PDF] [Slides (PPT)]
     Tuyen N. Huynh and Raymond J. Mooney
     In Proceedings of the European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML PKDD), Part 1, 564--579, Bled, Slovenia, September 2009.
197. Learning to Disambiguate Search Queries from Short Sessions
     [Details] [PDF]
     Lilyana Mihalkova and Raymond Mooney
     In Proceedings of the European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML PKDD), Part 2, 111--127, Bled, Slovenia, September 2009.
198. Max-Margin Weight Learning for Markov Logic Networks
     [Details] [PDF]
     Tuyen N. Huynh and Raymond J. Mooney
     In Proceedings of the International Workshop on Statistical Relational Learning (SRL-09), Leuven, Belgium, July 2009.
199. Speeding up Inference In Statistical Relational Learning by Clustering Similar Query Literals
     [Details] [PDF]
     Lilyana Mihalkova and Matthew Richardson
     In Proceedings of the 19th International Conference on Inductive Logic Programming (ILP-09), Leuven, Belgium, July 2009.
200. Learning a Compositional Semantic Parser using an Existing Syntactic Parser
     [Details] [PDF] [Slides (PPT)]
     Ruifang Ge and Raymond J. Mooney
     In Joint Conference of the 47th Annual Meeting of the Association for Computational Linguistics and the 4th International Joint Conference on Natural Language Processing of the Asian Federation of Natural Language Processing (ACL-IJCNLP 2009), 611--619, Suntec, Singapore, August 2009.
201. Probabilistic Abduction using Markov Logic Networks
     [Details] [PDF] [Slides (PPT)]
     Rohit J. Kate and Raymond J. Mooney
     In Proceedings of the IJCAI-09 Workshop on Plan, Activity, and Intent Recognition (PAIR-09), Pasadena, CA, July 2009.
202. Transfer Learning from Minimal Target Data by Mapping across Relational Domains
     [Details] [PDF]
     Lilyana Mihalkova and Raymond Mooney
     In Proceedings of the 21st International Joint Conference on Artificial Intelligence (IJCAI-09), 1163--1168, Pasadena, CA, July 2009.
203. Using Closed Captions to Train Activity Recognizers that Improve Video Retrieval
     [Details] [PDF]
     Sonal Gupta and Raymond Mooney
     In Proceedings of the CVPR-09 Workshop on Visual and Contextual Learning from Annotated Images and Videos (VCL), Miami, FL, June 2009.
204. Semi-supervised graph clustering: a kernel approach
     [Details] [PDF]
     Brian Kulis, Sugato Basu, Inderjit Dhillon, and Raymond Mooney
     Machine Learning Journal, 74(1):1-22, 2009.
205. Search Query Disambiguation from Short Sessions
     [Details] [PDF]
     Lilyana Mihalkova and Raymond Mooney
     In Beyond Search: Computational Intelligence for the Web Workshop at NIPS, 2008.
206. A Dependency-based Word Subsequence Kernel
     [Details] [PDF]
     Rohit J. Kate
     In Proceedings of the conference on Empirical Methods in Natural Language Processing (EMNLP-2008), 400--409, Waikiki, Honolulu, Hawaii, October 2008.
207. Transforming Meaning Representation Grammars to Improve Semantic Parsing
     [Details] [PDF]
     Rohit J. Kate
     In Proceedings of the Twelfth Conference on Computational Natural Language Learning (CoNLL-2008), 33--40, Manchester, UK, August 2008.
208. Watch, Listen & Learn: Co-training on Captioned Images and Videos
     [Details] [PDF]
     Sonal Gupta, Joohyun Kim, Kristen Grauman and Raymond Mooney
     In Proceedings of the European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML/PKDD), 457--472, Antwerp Belgium, September 2008.
209. Discriminative Structure and Parameter Learning for Markov Logic Networks
     [Details] [PDF] [Slides (PPT)]
     Tuyen N. Huynh and Raymond J. Mooney
     In Proceedings of the 25th International Conference on Machine Learning (ICML), Helsinki, Finland, July 2008.
210. Learning to Sportscast: A Test of Grounded Language Acquisition
     [Details] [PDF] [Slides (PPT)] [Video]
     David L. Chen and Raymond J. Mooney
     In Proceedings of the 25th International Conference on Machine Learning (ICML), Helsinki, Finland, July 2008.
211. Transfer Learning by Mapping with Minimal Target Data
     [Details] [PDF]
     Lilyana Mihalkova and Raymond J. Mooney
     In Proceedings of the AAAI-08 Workshop on Transfer Learning For Complex Tasks, Chicago, IL, July 2008.
212. Learning to Connect Language and Perception
     [Details] [PDF]
     Raymond J. Mooney
     In Proceedings of the 23rd AAAI Conference on Artificial Intelligence (AAAI), 1598--1601, Chicago, IL, July 2008. Senior Member Paper.
213. Improving Learning of Markov Logic Networks using Transfer and Bottom-Up Induction
     [Details] [PDF]
     Lilyana Mihalkova
     Technical Report UT-AI-TR-07-341, Artificial Intelligence Lab, University of Texas at Austin, Austin, TX, May 2007.
214. Learning for Semantic Parsing with Kernels under Various Forms of Supervision
     [Details] [PDF] [Slides (PPT)]
     Rohit J. Kate
     PhD Thesis, Department of Computer Sciences, University of Texas at Austin, Austin, TX, August 2007. 159 pages.
215. Learning for Semantic Parsing and Natural Language Generation Using Statistical Machine Translation Techniques
     [Details] [PDF]
     Yuk Wah Wong
     PhD Thesis, Department of Computer Sciences, University of Texas at Austin, Austin, TX, August 2007. 188 pages. Also appears as Technical Report AI07-343, Artificial Intelligence Lab, University of Texas at Austin, August 2007.
216. Learning for Information Extraction: From Named Entity Recognition and Disambiguation To Relation Extraction
     [Details] [PDF]
     Razvan Constantin Bunescu
     PhD Thesis, Department of Computer Sciences, University of Texas at Austin, Austin, TX, August 2007. 150 pages. Also as Technical Report AI07-345, Artificial Intelligence Lab, University of Texas at Austin, August 2007.
217. Learning to Extract Relations from the Web using Minimal Supervision
     [Details] [PDF]
     Razvan C. Bunescu and Raymond J. Mooney
     In Proceedings of the 45th Annual Meeting of the Association for Computational Linguistics (ACL'07), Prague, Czech Republic, June 2007.
218. Mapping and Revising Markov Logic Networks for Transfer Learning
     [Details] [PDF]
     Lilyana Mihalkova, Tuyen N. Huynh, Raymond J. Mooney
     In Proceedings of the Twenty-Second Conference on Artificial Intelligence (AAAI-07), 608-614, Vancouver, BC, July 2007.
219. Bottom-Up Learning of Markov Logic Network Structure
     [Details] [PDF]
     Lilyana Mihalkova and Raymond J. Mooney
     In Proceedings of 24th International Conference on Machine Learning (ICML-2007), Corvallis, OR, June 2007.
220. Multiple Instance Learning for Sparse Positive Bags
     [Details] [PDF]
     Razvan C. Bunescu and Raymond J. Mooney
     In Proceedings of the 24th Annual International Conference on Machine Learning (ICML-2007), Corvallis, OR, June 2007.
221. Learning Language Semantics from Ambiguous Supervision
     [Details] [PDF]
     Rohit J. Kate and Raymond J. Mooney
     In Proceedings of the 22nd Conference on Artificial Intelligence (AAAI-07), 895-900, Vancouver, Canada, July 2007.
222. Learning Synchronous Grammars for Semantic Parsing with Lambda Calculus
     [Details] [PDF]
     Yuk Wah Wong and Raymond J. Mooney
     In Proceedings of the 45th Annual Meeting of the Association for Computational Linguistics (ACL-2007), Prague, Czech Republic, June 2007.
223. Semi-Supervised Learning for Semantic Parsing using Support Vector Machines
     [Details] [PDF] [Slides (PPT)]
     Rohit J. Kate and Raymond J. Mooney
     In Proceedings of the Human Language Technology Conference of the North American Chapter of the Association for Computational Linguistics, Short Papers (NAACL/HLT-2007), 81--84, Rochester, NY, April 2007.
224. Generation by Inverting a Semantic Parser That Uses Statistical Machine Translation
     [Details] [PDF]
     Yuk Wah Wong and Raymond J. Mooney
     In Proceedings of Human Language Technologies: The Conference of the North American Chapter of the Association for Computational Linguistics (NAACL-HLT-07), 172-179, Rochester, NY, 2007.
225. Learning for Semantic Parsing
     [Details] [PDF]
     Raymond J. Mooney
     In A. Gelbukh, editors, Computational Linguistics and Intelligent Text Processing: Proceedings of the 8th International Conference (CICLing 2007), 311--324, Mexico City, Mexico, February 2007. Springer: Berlin, Germany. Invited paper.
226. Extracting Relations from Text: From Word Sequences to Dependency Paths
     [Details] [PDF]
     Razvan C. Bunescu and Raymond J. Mooney
     In A. Kao and S. Poteet, editors, Natural Language Processing and Text Mining, 29-44, Berlin, 2007. Springer Verlag.
227. Statistical Relational Learning for Natural Language Information Extraction
     [Details] [PDF]
     Razvan Bunescu and Raymond J. Mooney
     In L. Getoor and B. Taskar, editors, Introduction to Statistical Relational Learning, 535-552, Cambridge, MA, 2007. MIT Press.
228. Adaptive Blocking: Learning to Scale Up Record Linkage
     [Details] [PDF]
     Mikhail Bilenko, Beena Kamath, Raymond J. Mooney
     In Proceedings of the Sixth IEEE International Conference on Data Mining (ICDM-06), 87--96, Hong Kong, December 2006.
229. Fast and Effective Worm Fingerprinting via Machine Learning
     [Details] [PDF]
     Stewart Yang, Jianping Song, Harish Rajamani, Taewon Cho, Yin Zhang and Raymond Mooney
     In Proceedings of the 3rd IEEE International Conference on Autonomic Computing (ICAC-2006), Dublin, Ireland, June 2006. Poster Session.
230. Learnable Similarity Functions and Their Application to Record Linkage and Clustering
     [Details] [PDF]
     Mikhail Bilenko
     PhD Thesis, Department of Computer Sciences, University of Texas at Austin, Austin, TX, August 2006. 136 pages.
231. Learning Language from Perceptual Context: A Challenge Problem for AI
     [Details] [PDF]
     Raymond J. Mooney
     In Proceedings of the 2006 AAAI Fellows Symposium, Boston, MA, July 2006.
232. Using String-Kernels for Learning Semantic Parsers
     [Details] [PDF] [Slides (PPT)]
     Rohit J. Kate and Raymond J. Mooney
     In ACL 2006: Proceedings of the 21st International Conference on Computational Linguistics and the 44th annual meeting of the ACL, 913-920, Morristown, NJ, USA, 2006. Association for Computational Linguistics.
233. Discriminative Reranking for Semantic Parsing
     [Details] [PDF]
     Ruifang Ge and Raymond J. Mooney
     In Proceedings of the 21st International Conference on Computational Linguistics and 44th Annual Meeting of the Association for Computational Linguistics (COLING/ACL-06), Sydney, Australia, July 2006.
234. Transfer Learning with Markov Logic Networks
     [Details] [PDF]
     Lilyana Mihalkova and Raymond Mooney
     In Proceedings of the ICML-06 Workshop on Structural Knowledge Transfer for Machine Learning, Pittsburgh, PA, June 2006.
235. Integrating Co-occurrence Statistics with Information Extraction for Robust Retrieval of Protein Interactions from Medline
     [Details] [PDF]
     Razvan Bunescu, Raymond Mooney, Arun Ramani and Edward Marcotte
     In Proceedings of the HLT-NAACL Workshop on Linking Natural Language Processing and Biology (BioNLP'06), 49-56, New York, NY, June 2006.
236. Learning for Semantic Parsing with Statistical Machine Translation
     [Details] [PDF]
     Yuk Wah Wong and Raymond J. Mooney
     In Proceedings of Human Language Technology Conference / North American Chapter of the Association for Computational Linguistics Annual Meeting (HLT-NAACL-06), 439-446, New York City, NY, 2006.
237. Using Encyclopedic Knowledge for Named Entity Disambiguation
     [Details] [PDF]
     Razvan Bunescu and Marius Pasca
     In Proceesings of the 11th Conference of the European Chapter of the Association for Computational Linguistics (EACL-06), 9-16, Trento, Italy, 2006.
238. Learning Semantic Parsers Using Statistical Syntactic Parsing Techniques
     [Details] [PDF]
     Ruifang Ge
     2006. Doctoral Dissertation Proposal, University of Texas at Austin" , year="2006.
239. Fast and Effective Worm Fingerprinting via Machine Learning
     [Details] [PDF]
     Stewart Yang, Jianping Song, Harish Rajamani, Taewon Cho, Yin Zhang and Raymond Mooney
     Technical Report AI-06-335, Artificial Intelligence Lab, The University of Texas at Austin, August 2006. This is a longer version of our ICAC-2006 paper.
240. Probabilistic Semi-Supervised Clustering with Constraints
     [Details] [PDF]
     Sugato Basu, Mikhail Bilenko, Arindam Banerjee and Raymond J. Mooney
     In O. Chapelle and B. Sch{"{o}}lkopf and A. Zien, editors, Semi-Supervised Learning, Cambridge, MA, 2006. MIT Press.
241. Subsequence Kernels for Relation Extraction
     [Details] [PDF]
     Razvan Bunescu and Raymond J. Mooney
     In Y. Weiss, B. Schoelkopf, J. Platt, editors, Advances in Neural Information Processing Systems, Vol. 18: Proceedings of the 2005 Conference (NIPS), 2006.
242. Using Active Relocation to Aid Reinforcement Learning
     [Details] [PDF]
     Lilyana Mihalkova and Raymond Mooney
     In Prodeedings of the 19th International FLAIRS Conference (FLAIRS-2006), 580-585, Melbourne Beach, FL, May 2006.
243. Creating Diverse Ensemble Classifiers to Reduce Supervision
     [Details] [PDF]
     Prem Melville
     PhD Thesis, Department of Computer Sciences, University of Texas at Austin, November 2005. 141 pages. Technical Report TR-05-49.
244. A Kernel-based Approach to Learning Semantic Parsers
     [Details] [PDF] [Slides (PPT)]
     Rohit J. Kate
     2005. Doctoral Dissertation Proposal, University of Texas at Austin.
245. Learning for Semantic Parsing Using Statistical Machine Translation Techniques
     [Details] [PDF]
     Yuk Wah Wong
     2005. Doctoral Dissertation Proposal, University of Texas at Austin.
246. An Expected Utility Approach to Active Feature-value Acquisition
     [Details] [PDF]
     P. Melville, M. Saar-Tsechansky, F. Provost and Raymond J. Mooney
     In Proceedings of the International Conference on Data Mining, 745-748, Houston, TX, November 2005.
247. Combining Bias and Variance Reduction Techniques for Regression
     [Details] [PDF]
     Yuk Lai Suen, Prem Melville and Raymond J. Mooney
     Technical Report UT-AI-TR-05-321, University of Texas at Austin, July 2005. www.cs.utexas.edu/~ml/publication.
248. Adaptive Product Normalization: Using Online Learning for Record Linkage in Comparison Shopping
     [Details] [PDF]
     Mikhail Bilenko, Sugato Basu, and Mehran Sahami
     In Proceedings of the 5th International Conference on Data Mining (ICDM-2005), 58--65, Houston, TX, November 2005.
249. Alignments and String Similarity in Information Integration: A Random Field Approach
     [Details] [PDF]
     Mikhail Bilenko and Raymond J. Mooney
     In Proceedings of the 2005 Dagstuhl Seminar on Machine Learning for the Semantic Web, Dagstuhl, Germany, February 2005.
250. A Shortest Path Dependency Kernel for Relation Extraction
     [Details] [PDF]
     R. C. Bunescu, and Raymond J. Mooney
     In Proceedings of the Human Language Technology Conference and Conference on Empirical Methods in Natural Language Processing (HLT/EMNLP-05), 724-731, Vancouver, BC, October 2005.
251. Semi-supervised Clustering: Probabilistic Models, Algorithms and Experiments
     [Details] [PDF]
     Sugato Basu
     PhD Thesis, University of Texas at Austin, 2005.
252. Combining Bias and Variance Reduction Techniques for Regression
     [Details] [PDF]
     Y. L. Suen, P. Melville and Raymond J. Mooney
     In Proceedings of the 16th European Conference on Machine Learning, 741-749, Porto, Portugal, October 2005.
253. Consolidating the Set of Known Human Protein-Protein Interactions in Preparation for Large-Scale Mapping of the Human Interactome
     [Details] [PDF]
     A.K. Ramani, R.C. Bunescu, Raymond J. Mooney and E.M. Marcotte
     Genome Biology, 6(5):r40, 2005.
254. A Statistical Semantic Parser that Integrates Syntax and Semantics
     [Details] [PDF]
     Ruifang Ge and Raymond J. Mooney
     In Proceedings of CoNLL-2005, Ann Arbor, Michigan, June 2005.
255. Mining Knowledge from Text Using Information Extraction
     [Details] [PDF]
     Raymond J. Mooney and R. Bunescu
     SIGKDD Explorations (special issue on Text Mining and Natural Language Processing), 7(1):3-10, 2005.
256. Economical Active Feature-value Acquisition through Expected Utility Estimation
     [Details] [PDF]
     P. Melville, M. Saar-Tsechansky, F. Provost and Raymond J. Mooney
     In Proceedings of the KDD-05 Workshop on Utility-Based Data Mining, 10-16, Chicago, IL, August 2005.
257. Semi-supervised Graph Clustering: A Kernel Approach
     [Details] [PDF]
     B. Kulis, S. Basu, I. Dhillon and Raymond J. Mooney
     In Proceedings of the 22nd International Conference on Machine Learning, 457--464, Bonn, Germany, August 2005. (Distinguished Student Paper Award).
258. Using Biomedical Literature Mining to Consolidate the Set of Known Human Protein-Protein Interactions
     [Details] [PDF]
     A. Ramani, E. Marcotte, R. Bunescu and Raymond J. Mooney
     In Proceedings of the ISMB/ACL-05 Workshop of the BioLINK SIG: Linking Literature, Information and Knowledge for Biology, Detroit, MI, June 2005.
259. Model-based Overlapping Clustering
     [Details] [PDF]
     A. Banerjee, C. Krumpelman, S. Basu, Raymond J. Mooney and Joydeep Ghosh
     In Proceedings of the Eleventh ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD-05), 2005.
260. Towards Self-Configuring Hardware for Distributed Computer Systems
     [Details] [PDF]
     Jonathan Wildstrom, Peter Stone, E. Witchel, Raymond Mooney and M. Dahlin
     In The Second International Conference on Autonomic Computing, 241-249, June 2005.
261. Active Learning for Probability Estimation using Jensen-Shannon Divergence
     [Details] [PDF]
     P. Melville, S. M. Yang, M. Saar-Tsechansky and Raymond J. Mooney
     In Proceedings of the 16th European Conference on Machine Learning, 268--279, Porto, Portugal, October 2005.
262. Learning to Transform Natural to Formal Languages
     [Details] [PDF] [Slides (PPT)]
     Rohit J. Kate, Yuk Wah Wong and Raymond J. Mooney
     In Proceedings of the Twentieth National Conference on Artificial Intelligence (AAAI-05), 1062-1068, Pittsburgh, PA, July 2005.
263. Explaining Recommendations: Satisfaction vs. Promotion
     [Details] [PDF]
     Mustafa Bilgic and Raymond J. Mooney
     In Proceedings of Beyond Personalization 2005: A Workshop on the Next Stage of Recommender Systems Research at the 2005 International Conference on Intelligent User Interfaces, San Diego, CA, January 2005.
264. Learning for Collective Information Extraction
     [Details] [PDF]
     Razvan C. Bunescu
     Technical Report TR-05-02, Department of Computer Sciences, University of Texas at Austin, October 2005. Ph.D. proposal.
265. Comparative Experiments on Learning Information Extractors for Proteins and their Interactions
     [Details] [PDF]
     Razvan Bunescu, Ruifang Ge, Rohit J. Kate, Edward M. Marcotte, Raymond J. Mooney, Arun Kumar Ramani, and Yuk Wah Wong
     Artificial Intelligence in Medicine (special issue on Summarization and Information Extraction from Medical Documents)(2):139-155, 2005.
266. Active Feature-Value Acquisition for Classifier Induction
     [Details] [PDF]
     Prem Melville, Maytal Saar-Tsechansky, Foster Provost, and Raymond J. Mooney
     Technical Report UT-AI-TR-04-311, Artificial Intelligence Lab, University of Texas at Austin, February 2004.
267. Active Feature-Value Acquisition for Classifier Induction
     [Details] [PDF]
     Prem Melville, Maytal Saar-Tsechansky, Foster Provost, and Raymond J. Mooney
     In Proceedings of the Fourth IEEE International Conference on Data Mining (ICDM-2004), 483-486, Brighton, UK, November 2004.
268. A Probabilistic Framework for Semi-Supervised Clustering
     [Details] [PDF]
     Sugato Basu, Mikhail Bilenko, and Raymond J. Mooney
     In Proceedings of the Tenth ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD-2004), 59-68, Seattle, WA, August 2004.
269. Text Mining with Information Extraction
     [Details] [PDF]
     Un Yong Nahm
     PhD Thesis, Department of Computer Sciences, University of Texas at Austin, Austin, TX, August 2004. 217 pages. Also appears as Technical Report UT-AI-TR-04-311.
270. Collective Information Extraction with Relational Markov Networks
     [Details] [PDF]
     Razvan Bunescu and Raymond J. Mooney
     In Proceedings of the 42nd Annual Meeting of the Association for Computational Linguistics (ACL-04), 439-446, Barcelona, Spain, July 2004.
271. Guiding a Reinforcement Learner with Natural Language Advice: Initial Results in RoboCup Soccer
     [Details] [PDF]
     Gregory Kuhlmann, Peter Stone, Raymond J. Mooney, and Jude W. Shavlik
     In The AAAI-2004 Workshop on Supervisory Control of Learning and Adaptive Systems, July 2004.
272. Using Soft-Matching Mined Rules to Improve Information Extraction
     [Details] [PDF]
     Un Yong Nahm and Raymond J. Mooney
     In Proceedings of the AAAI-2004 Workshop on Adaptive Text Extraction and Mining (ATEM-2004), 27-32, San Jose, CA, July 2004.
273. Semi-supervised Clustering with Limited Background Knowledge
     [Details] [PDF]
     Sugato Basu
     In Proceedings of the Ninth AAAI/SIGART Doctoral Consortium, 979--980, San Jose, CA, July 2004.
274. Learnable Similarity Functions and Their Applications to Clustering and Record Linkage
     [Details] [PDF]
     Mikhail Bilenko
     In Proceedings of the Ninth AAAI/SIGART Doctoral Consortium, 981--982, San Jose, CA, July 2004.
275. Integrating Constraints and Metric Learning in Semi-Supervised Clustering
     [Details] [PDF]
     Mikhail Bilenko, Sugato Basu, and Raymond J. Mooney
     In Proceedings of 21st International Conference on Machine Learning (ICML-2004), 81-88, Banff, Canada, July 2004.
276. Diverse Ensembles for Active Learning
     [Details] [PDF]
     Prem Melville and Raymond J. Mooney
     In Proceedings of 21st International Conference on Machine Learning (ICML-2004), 584-591, Banff, Canada, July 2004.
277. Relational Markov Networks for Collective Information Extraction
     [Details] [PDF]
     Razvan Bunescu and Raymond J. Mooney
     In Proceedings of the ICML-04 Workshop on Statistical Relational Learning and its Connections to Other Fields, Banff, Alberta, July 2004.
278. A Comparison of Inference Techniques for Semi-supervised Clustering with Hidden Markov Random Fields
     [Details] [PDF]
     Mikhail Bilenko and Sugato Basu
     In Proceedings of the ICML-2004 Workshop on Statistical Relational Learning and its Connections to Other Fields (SRL-2004), Banff, Canada, July 2004.
279. Experiments on Ensembles with Missing and Noisy Data
     [Details] [PDF]
     Prem Melville, Nishit Shah, Lilyana Mihalkova, and Raymond J. Mooney
     In F. Roli, J. Kittler, and T. Windeatt, editors, {Lecture Notes in Computer Science:} Proceedings of the Fifth International Workshop on Multi Classifier Systems (MCS-2004), 293-302, Cagliari, Italy, June 2004. Springer Verlag.
280. Explanation for Recommender Systems: Satisfaction vs. Promotion
     [Details] [PDF]
     Mustafa Bilgic
     Austin, TX, May 2004. Undergraduate Honor Thesis, Department of Computer Sciences, University of Texas at Austin.
281. Active Semi-Supervision for Pairwise Constrained Clustering
     [Details] [PDF]
     Sugato Basu, Arindam Banerjee, and Raymond J. Mooney
     In Proceedings of the 2004 SIAM International Conference on Data Mining (SDM-04), April 2004.
282. Learning Transformation Rules for Semantic Parsing
     [Details] [PDF]
     Rohit J. Kate, Yuk Wah Wong, Ruifang Ge, and Raymond J. Mooney
     April 2004. Unpublished Technical Report.
283. Creating Diversity in Ensembles Using Artificial Data
     [Details] [PDF]
     Prem Melville and Raymond J. Mooney
     Journal of Information Fusion: Special Issue on Diversity in Multi Classifier Systems, 6(1):99-111, 2004.
284. Learning Semantic Parsers: An Important But Under-Studied Problem
     [Details] [PDF]
     Raymond J. Mooney
     In Papers from the AAAI 2004 Spring Symposium on Language Learning: An Interdisciplinary Perspective, 39--44, Stanford, CA, March 2004.
285. Relational Data Mining with Inductive Logic Programming for Link Discovery
     [Details] [PDF]
     Raymond J. Mooney, P. Melville, L. R. Tang, J. Shavlik, I. Dutra and D. Page
     Kargupta, H., Joshi, A., Sivakumar K., and Yesha, Y., editors, Data Mining: Next Generation Challenges and Future Directions:239--254, Menlo Park, CA, 2004. AAAI Press.
286. Semisupervised Clustering for Intelligent User Management
     [Details] [PDF]
     Sugato Basu, Mikhail Bilenko, and Raymond J. Mooney
     In Proceedings of the IBM Austin Center for Advanced Studies 5th Annual Austin CAS Conference, Austin, TX, February 2004.
287. Semi-supervised Clustering: Learning with Limited User Feedback
     [Details] [PDF]
     Sugato Basu
     Technical Report, Cornell University, 2004.
288. Text Mining with Information Extraction
     [Details] [PDF]
     Raymond J. Mooney and Un Yong Nahm
     In W. Daelemans and T. du Plessis and C. Snyman and L. Teck, editors, Multilingualism and Electronic Language Management: Proceedings of the 4th International MIDP Colloquium, 141-160, Bloemfontein, South Africa, September 2003. Van Schaik: South Africa.
289. Learnable Similarity Functions and Their Applications to Record Linkage and Clustering
     [Details] [PDF]
     Mikhail Bilenko
     2003. Doctoral Dissertation Proposal, University of Texas at Austin.
290. Creating Diverse Ensemble Classifiers
     [Details] [PDF]
     Prem Melville
     Technical Report UT-AI-TR-03-306, Department of Computer Sciences, University of Texas at Austin, December 2003. Ph.D. proposal.
291. Adaptive Name-Matching in Information Integration
     [Details] [PDF]
     Mikhail Bilenko, William W. Cohen, Stephen Fienberg, Raymond J. Mooney, and Pradeep Ravikumar
     IEEE Intelligent Systems, 18(5):16-23, 2003.
292. Integrating Top-down and Bottom-up Approaches in Inductive Logic Programming: Applications in Natural Language Processing and Relational Data Mining
     [Details] [PDF]
     Lappoon R. Tang
     PhD Thesis, Department of Computer Sciences, University of Texas, Austin, TX, August 2003.
293. On Evaluation and Training-Set Construction for Duplicate Detection
     [Details] [PDF]
     Mikhail Bilenko and Raymond J. Mooney
     In Proceedings of the KDD-03 Workshop on Data Cleaning, Record Linkage, and Object Consolidation, 7-12, Washington, DC, August 2003.
294. Scaling Up ILP to Large Examples: Results on Link Discovery for Counter-Terrorism
     [Details] [PDF]
     Lappoon R. Tang, Raymond J. Mooney, and Prem Melville
     In Proceedings of the KDD-2003 Workshop on Multi-Relational Data Mining (MRDM-2003), 107--121, Washington DC, August 2003.
295. Adaptive Duplicate Detection Using Learnable String Similarity Measures
     [Details] [PDF]
     Mikhail Bilenko and Raymond J. Mooney
     In Proceedings of the Ninth ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD-2003), 39-48, Washington, DC, August 2003.
296. Learning to Extract Proteins and their Interactions from Medline Abstracts
     [Details] [PDF]
     Razvan Bunescu, Ruifang Ge, Rohit J. Kate, Raymond J. Mooney, Yuk Wah Wong, Edward M. Marcotte, and Arun Kumar Ramani
     In Proceedings of the ICML-03 Workshop on Machine Learning in Bioinformatics, 46-53, Washington, DC, August 2003.
297. Comparing and Unifying Search-Based and Similarity-Based Approaches to Semi-Supervised Clustering
     [Details] [PDF]
     Sugato Basu, Mikhail Bilenko, and Raymond J. Mooney
     In Proceedings of the ICML-2003 Workshop on the Continuum from Labeled to Unlabeled Data in Machine Learning and Data Mining, 42-49, Washington, DC, 2003.
298. Bottom-Up Relational Learning of Pattern Matching Rules for Information Extraction
     [Details] [PDF]
     Mary Elaine Califf and Raymond J. Mooney
     Journal of Machine Learning Research:177-210, 2003.
299. Employing Trainable String Similarity Metrics for Information Integration
     [Details] [PDF]
     Mikhail Bilenko and Raymond J. Mooney
     In Proceedings of the IJCAI-03 Workshop on Information Integration on the Web, 67-72, Acapulco, Mexico, August 2003.
300. Constructing Diverse Classifier Ensembles Using Artificial Training Examples
     [Details] [PDF]
     Prem Melville and Raymond J. Mooney
     In Proceedings of the Eighteenth International Joint Conference on Artificial Intelligence (IJCAI-2003), 505-510, Acapulco, Mexico, August 2003.
301. Acquiring Word-Meaning Mappings for Natural Language Interfaces
     [Details] [PDF]
     Cynthia A. Thompson and Raymond J. Mooney
     Journal of Artificial Intelligence Research, 18:1-44, 2003.
302. Associative Anaphora Resolution: A Web-Based Approach
     [Details] [PDF]
     Razvan Bunescu
     In Proceedings of the EACL-2003 Workshop on the Computational Treatment of Anaphora, 47-52, Budapest, Hungary, 2003.
303. Machine Learning
     [Details] [PDF]
     Raymond J. Mooney
     New York, NY, 2003. McGraw-Hill.
304. Property-Based Feature Engineering and Selection
     [Details] [PDF]
     Noppadon Kamolvilassatian
     Masters Thesis, Department of Computer Sciences, University of Texas at Austin, Austin, TX, December 2002. 85 pages.
305. Mining Soft-Matching Association Rules
     [Details] [PDF]
     Un Yong Nahm and Raymond J. Mooney
     In Proceedings of the Eleventh International Conference on Information and Knowledge Management (CIKM-2002), 681-683, McLean, VA, November 2002.
306. Relational Data Mining with Inductive Logic Programming for Link Discovery
     [Details] [PDF]
     Raymond J. Mooney, Prem Melville, Lappoon R. Tang, Jude Shavlik, Inês de Castro Dutra, David Page, and Vítor Santos Costa
     In Proceedings of the National Science Foundation Workshop on Next Generation Data Mining, Baltimore, MD, November 2002.
307. Two Approaches to Handling Noisy Variation in Text Mining
     [Details] [PDF]
     Un Yong Nahm, Mikhail Bilenko, and Raymond J. Mooney
     In Papers from the Nineteenth International Conference on Machine Learning (ICML-2002) Workshop on Text Learning, 18-27, Sydney, Australia, July 2002.
308. Content-Boosted Collaborative Filtering for Improved Recommendations
     [Details] [PDF]
     Prem Melville, Raymond J. Mooney, and Ramadass Nagarajan
     In Proceedings of the Eighteenth National Conference on Artificial Intelligence (AAAI-02), 187-192, Edmonton, Alberta, 2002.
309. Semi-supervised Clustering by Seeding
     [Details] [PDF]
     Sugato Basu, Arindam Banerjee, and Raymond J. Mooney
     In Proceedings of 19th International Conference on Machine Learning (ICML-2002), 19-26, 2002.
310. Text Mining with Information Extraction
     [Details] [PDF]
     Un Yong Nahm and Raymond J. Mooney
     In Proceedings of the AAAI 2002 Spring Symposium on Mining Answers from Texts and Knowledge Bases, 60-67, Stanford, CA, March 2002.
311. Extracting Gene and Protein Names from Biomedical Abstracts
     [Details] [PDF]
     Razvan Bunescu, Ruifang Ge, Raymond J. Mooney, Edward Marcotte, and Arun Kumar Ramani
     March 2002. Unpublished Technical Note.
312. Learning to Combine Trained Distance Metrics for Duplicate Detection in Databases
     [Details] [PDF]
     Mikhail Bilenko and Raymond J. Mooney
     Technical Report AI 02-296, Artificial Intelligence Laboratory, University of Texas at Austin, Austin, TX, February 2002.
313. ELIXIR: A Library for Writing Wrappers in Java
     [Details] [PDF]
     Edward Wild
     December 2001. Undergraduate Honor Thesis, Department of Computer Sciences, University of Texas at Austin.
314. Content-Boosted Collaborative Filtering
     [Details] [PDF]
     Prem Melville, Raymond J. Mooney, and Ramadass Nagarajan
     In Proceedings of the SIGIR-2001 Workshop on Recommender Systems, New Orleans, LA, September 2001.
315. Using Multiple Clause Constructors in Inductive Logic Programming for Semantic Parsing
     [Details] [PDF]
     Lappoon R. Tang and Raymond J. Mooney
     In Proceedings of the 12th European Conference on Machine Learning, 466-477, Freiburg, Germany, 2001.
316. Evaluating the Novelty of Text-Mined Rules using Lexical Knowledge
     [Details] [PDF]
     Sugato Basu, Raymond J. Mooney, Krupakar V. Pasupuleti, and Joydeep Ghosh
     In Proceedings of the Seventh ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD-2001), 233-239, San Francisco, CA, 2001.
317. Mining Soft-Matching Rules from Textual Data
     [Details] [PDF]
     Un Yong Nahm and Raymond J. Mooney
     In Proceedings of the 18th International Joint Conference on Artificial Intelligence, 2001.
318. Using Lexical Knowlege to Evaluate the Novelty of Rules Mined from Text
     [Details] [PDF]
     Sugato Basu, Raymond J. Mooney, Krupakar V. Pasupuleti, and Joydeep Ghosh
     In Proceedings of NAACL 2001 Workshop on WordNet and Other Lexical Resources: Applications, Extensions and Customizations, 144--149, Pittsburg, PA, June 2001.
319. Text Mining with Information Extraction
     [Details] [PDF]
     Un Yong Nahm
     February 2001. Ph.D. proposal, Department of Computer Sciences, University of Texas at Austin.
320. Automated Construction of Database Interfaces: Integrating Statistical and Relational Learning for Semantic Parsing
     [Details] [PDF]
     Lappoon R. Tang and Raymond J. Mooney
     In Proceedings of the Joint SIGDAT Conference on Empirical Methods in Natural Language Processing and Very Large Corpora(EMNLP/VLC-2000), 133-141, Hong Kong, October 2000.
321. Using Information Extraction to Aid the Discovery of Prediction Rules from Text
     [Details] [PDF]
     Un Yong Nahm and Raymond J. Mooney
     In Proceedings of the Sixth International Conference on Knowledge Discovery and Data Mining (KDD-2000) Workshop on Text Mining, 51--58, Boston, MA, August 2000.
322. A Mutually Beneficial Integration of Data Mining and Information Extraction
     [Details] [PDF]
     Un Yong Nahm and Raymond J. Mooney
     In Proceedings of the Seventeenth National Conference on Artificial Intelligence (AAAI-00), 627-632, Austin, TX, July 2000.
323. Integrating Statistical and Relational Learning for Semantic Parsing: Applications to Learning Natural Language Interfaces for Databases
     [Details] [PDF]
     Lappoon R. Tang
     May 2000. Ph.D. proposal, Department of Computer Sciences, University of Texas at Austin.
324. Content-Based Book Recommending Using Learning for Text Categorization
     [Details] [PDF]
     Raymond J. Mooney and Loriene Roy
     In Proceedings of the Fifth ACM Conference on Digital Libraries, 195-204, San Antonio, TX, June 2000.
325. Integrating Abduction and Induction in Machine Learning
     [Details] [PDF]
     Raymond J. Mooney
     In P. A. Flach and A. C. Kakas, editors, Abduction and Induction, 181-191, 2000. Kluwer Academic Publishers.
326. Learning for Semantic Interpretation: Scaling Up Without Dumbing Down
     [Details] [PDF]
     Raymond J. Mooney
     In Workshop Notes for the Workshop on Learning Language in Logic, 7-15, Bled, Slovenia, 2000.
327. Content-Based Book Recommending Using Learning for Text Categorization
     [Details] [PDF]
     Raymond J. Mooney and Loriene Roy
     In Proceedings of the SIGIR-99 Workshop on Recommender Systems: Algorithms and Evaluation, Berkeley, CA, August 1999.
328. Automatic Construction of Semantic Lexicons for Learning Natural Language Interfaces
     [Details] [PDF]
     Cynthia A. Thompson and Raymond J. Mooney
     In Proceedings of the Sixteenth National Conference on Artificial Intelligence (AAAI-99), 487-493, Orlando, FL, July 1999.
329. Relational Learning of Pattern-Match Rules for Information Extraction
     [Details] [PDF]
     Mary Elaine Califf and Raymond J. Mooney
     In Proceedings of the Sixteenth National Conference on Artificial Intelligence (AAAI-99), 328-334, Orlando, FL, July 1999.
330. Active Learning for Natural Language Parsing and Information Extraction
     [Details] [PDF]
     Cynthia A. Thompson, Mary Elaine Califf and Raymond J. Mooney
     In Proceedings of the Sixteenth International Conference on Machine Learning (ICML-99), 406-414, Bled, Slovenia, June 1999.
331. Using HTML Structure and Linked Pages to Improve Learning for Text Categorization
     [Details] [PDF]
     Michael B. Cline
     Technical Report AI 98-270, Department of Computer Sciences, University of Texas at Austin, Austin, TX, May 1999. Undergraduate Honors Thesis.
332. Semantic Lexicon Acquisition for Learning Natural Language Interfaces
     [Details] [PDF]
     Cynthia Ann Thompson
     PhD Thesis, Department of Computer Sciences, University of Texas at Austin, Austin, TX, December 1998. 101 pages. Also appears as Technical Report AI 99-278, Artificial Intelligence Lab, University of Texas at Austin.
333. Semantic Lexicon Acquisition for Learning Natural Language Interfaces
     [Details] [PDF]
     Cynthia A. Thompson and Raymond J. Mooney
     In Proceedings of the Sixth Workshop on Very Large Corpora, Montreal, Quebec, Canada, August 1998. Also available as TR AI 98-273, Artificial Intelligence Lab, University of Texas at Austin, May 1998.
334. Relational Learning Techniques for Natural Language Information Extraction
     [Details] [PDF]
     Mary Elaine Califf
     PhD Thesis, Department of Computer Sciences, University of Texas, Austin, TX, August 1998. 142 pages. Also appears as Artificial Intelligence Laboratory Technical Report AI 98-276.
335. Theory Refinement for Bayesian Networks with Hidden Variables
     [Details] [PDF]
     Sowmya Ramachandran and Raymond J. Mooney
     In Proceedings of the Fifteenth International Conference on Machine Learning (ICML-98), 454--462, Madison, WI, July 1998.
336. Book Recommending Using Text Categorization with Extracted Information
     [Details] [PDF]
     Raymond J. Mooney, Paul N. Bennett, and Loriene Roy
     In Proceedings of the Fifteenth National Conference on Artificial Intelligence (AAAI-98)"-REC-WKSHP98, year="1998, 70-74, Madison, WI, 1998.
337. Text Categorization Through Probabilistic Learning: Applications to Recommender Systems
     [Details] [PDF]
     Paul N. Bennett
     1998. Honors thesis, Department of Computer Sciences, The University of Texas at Austin.
338. Theory Refinement of Bayesian Networks with Hidden Variables
     [Details] [PDF]
     Sowmya Ramachandran and Raymond J. Mooney
     PhD Thesis, Department of Computer Sciences, University of Texas at Austin, Austin, TX, May 1998. 139 pages. Also appears as Technical Report AI 98-265, Artificial Intelligence Lab, University of Texas at Austin.
339. An Experimental Comparison of Genetic Programming and Inductive Logic Programming on Learning Recursive List Functions
     [Details] [PDF]
     Lappoon R. Tang, Mary Elaine Califf, and Raymond J. Mooney
     Technical Report AI 98-271, Artificial Intelligence Lab, University of Texas at Austin, May 1998.
340. Advantages of Decision Lists and Implicit Negatives in Inductive Logic Programming
     [Details] [PDF]
     Mary Elaine Califf and Raymond J. Mooney
     New Generation Computing, 16(3):263-281, 1998.
341. Using Multi-Strategy Learning to Improve Planning Efficiency and Quality
     [Details] [PDF]
     Tara A. Estlin
     PhD Thesis, Department of Computer Sciences, The University of Texas at Austin, Austin, TX, 1998.
342. Relational Learning of Pattern-Match Rules for Information Extraction
     [Details] [PDF]
     Mary Elaine Califf and Raymond J. Mooney
     In Proceedings of AAAI Spring Symposium on Applying Machine Learning to Discourse Processing, 6-11, Standford, CA, March 1998.
343. Integrating Abduction and Induction in Machine Learning
     [Details] [PDF]
     Raymond J. Mooney
     In Working Notes of the IJCAI-97 Workshop on Abduction and Induction in AI, 37--42, Nagoya, Japan, August 1997.
344. Relational Learning Techniques for Natural Language Information Extraction
     [Details] [PDF]
     Mary Elaine Califf
     1997. Ph.D. proposal, Department of Computer Sciences, University of Texas at Austin.
345. Learning to Improve both Efficiency and Quality of Planning
     [Details] [PDF]
     Tara A. Estlin and Raymond J. Mooney
     In Proceedings of the Fifteenth International Joint Conference on Artificial Intelligence (IJCAI-97), 1227-1232, Nagoya, Japan, 1997.
346. Applying ILP-based Techniques to Natural Language Information Extraction: An Experiment in Relational Learning
     [Details] [PDF]
     Mary Elaine Califf and Raymond J. Mooney
     In Workshop Notes of the IJCAI-97 Workshop on Frontiers of Inductive Logic Programming, 7--11, Nagoya, Japan, August 1997.
347. Learning to Parse Natural Language Database Queries into Logical Form
     [Details] [PDF]
     Cynthia A. Thompson, Raymond J. Mooney, and Lappoon R. Tang
     In Proceedings of the ML-97 Workshop on Automata Induction, Grammatical Inference, and Language Acquisition, Nashville, TN, July 1997.
348. Relational Learning of Pattern-Match Rules for Information Extraction
     [Details] [PDF]
     Mary Elaine Califf and Raymond J. Mooney
     In Proceedings of the ACL Workshop on Natural Language Learning, 9-15, Madrid, Spain, July 1997.
349. Learning Parse and Translation Decisions From Examples With Rich Context
     [Details] [PDF]
     Ulf Hermjakob and Raymond J. Mooney
     In Proceedings of the 35th Annual Meeting of the Association for Computational Linguistics (ACL'97/EACL'97), 482-489, July 1997.
350. Learning Parse and Translation Decisions From Examples With Rich Context
     [Details] [PDF]
     Ulf Hermjakob
     PhD Thesis, Department of Computer Sciences, The University of Texas at Austin, Austin, TX, May 1997. 175 pages. Technical Report UT-AI97-261.
351. An Inductive Logic Programming Method for Corpus-based Parser Construction
     [Details] [PDF]
     John M. Zelle and Raymond J. Mooney
     January 1997. Unpublished Technical Note.
352. Parameter Revision Techniques for Bayesian Networks with Hidden Variables: An Experimental Comparison
     [Details] [PDF]
     Sowmya Ramachandran and Raymond J. Mooney
     January 1997. Unpublished Technical Note.
353. Semantic Lexicon Acquisition for Learning Parsers
     [Details] [PDF]
     Cynthia A. Thompson and Raymond J. Mooney
     1997. Submitted for review.
354. Inductive Logic Programming for Natural Language Processing
     [Details] [PDF]
     Raymond J. Mooney
     In Stephen Muggleton, editors, Inductive Logic Programming: Selected papers from the 6th International Workshop, 3-22, Berlin, 1996. Springer Verlag.
355. Integrating Explanation-Based and Inductive Learning Techniques to Acquire Search-Control for Planning
     [Details] [PDF]
     Tara A. Estlin
     Technical Report AI96-250, Department of Computer Sciences, University of Texas, Austin, TX, 1996.
356. Learning to Parse Database Queries using Inductive Logic Programming
     [Details] [PDF]
     John M. Zelle and Raymond J. Mooney
     In AAAI/IAAI, 1050-1055, Portland, OR, August 1996. AAAI Press/MIT Press.
357. A Novel Application of Theory Refinement to Student Modeling
     [Details] [PDF]
     Paul Baffes and Raymond J. Mooney
     In Proceedings of the Thirteenth National Conference on Artificial Intelligence (AAAI-96), 403-408, Portland, OR, August 1996.
358. Qualitative Multiple-Fault Diagnosis of Continuous Dynamic Systems Using Behavioral Modes
     [Details] [PDF]
     Siddarth Subramanian and Raymond J. Mooney
     In Proceedings of the Thirteenth National Conference on Artificial Intelligence (AAAI-96), 965-970, Portland, OR, August 1996.
359. Multi-Strategy Learning of Search Control for Partial-Order Planning
     [Details] [PDF]
     Tara A. Estlin and Raymond J. Mooney
     In Proceedings of the Thirteenth National Conference on Artificial Intelligence (AAAI-96), 843-848, Portland, OR, August 1996.
360. Comparative Experiments on Disambiguating Word Senses: An Illustration of the Role of Bias in Machine Learning
     [Details] [PDF]
     Raymond J. Mooney
     In Proceedings of the Conference on Empirical Methods in Natural Language Processing (EMNLP-96), 82-91, Philadelphia, PA, 1996.
361. Combining Symbolic and Connectionist Learning Methods to Refine Certainty-Factor Rule-Bases
     [Details] [PDF]
     J. Jeffrey Mahoney
     PhD Thesis, Department of Computer Sciences, University of Texas at Austin, May 1996. 113 pages.
362. Integrating EBL and ILP to Acquire Control Rules for Planning
     [Details] [PDF]
     Tara A. Estlin and Raymond J. Mooney
     In Proceedings of the Third International Workshop on Multi-Strategy Learning (MSL-96), 271--279, Harpers Ferry, WV, May 1996.
363. Refinement-Based Student Modeling and Automated Bug Library Construction
     [Details] [PDF]
     Paul Baffes and Raymond Mooney
     Journal of Artificial Intelligence in Education, 7(1):75-116, 1996.
364. Revising Bayesian Network Parameters Using Backpropagation
     [Details] [PDF]
     Sowmya Ramachandran and Raymond J. Mooney
     In Proceedings of the International Conference on Neural Networks (ICNN-96), Special Session on Knowledge-Based Artificial Neural Networks, 82--87, Washington DC, June 1996.
365. Corpus-Based Lexical Acquisition For Semantic Parsing
     [Details] [PDF]
     Cynthia Thompson
     February 1996. Ph.D. proposal.
366. Lexical Acquisition: A Novel Machine Learning Problem
     [Details] [PDF]
     Cynthia A. Thompson and Raymond J. Mooney
     Technical Report, Artificial Intelligence Lab, University of Texas at Austin, January 1996.
367. Advantages of Decision Lists and Implicit Negative in Inductive Logic Programming
     [Details] [PDF]
     Mary Elaine Califf and Raymond J. Mooney
     Technical Report, Artificial Intelligence Lab, University of Texas at Austin, January 1996.
368. Comparative Results on Using Inductive Logic Programming for Corpus-based Parser Construction
     [Details] [PDF]
     John M. Zelle and Raymond J. Mooney
     In Stefan Wermter and Ellen Riloff and Gabriela Scheler, editors, Connectionist, Statistical, and Symbolic Approaches to Learning for Natural Language Processing, 355-369, Berlin, 1996. Springer.
369. Learning the Past Tense of English Verbs Using Inductive Logic Programming
     [Details] [PDF]
     Raymond J. Mooney and Mary Elaine Califf
     In {S. Wermter, E. Riloff} and G. Scheler, editors, Connectionist, Statistical, and Symbolic Approaches to Learning for Natural Language Processing, 370-384, Berlin, 1996. Springer.
370. Hybrid Learning of Search Control for Partial-Order Planning
     [Details] [PDF]
     Tara A. Estlin and Raymond J. Mooney
     In Malik Ghallab and Alfredo Milani, editors, New Directions in AI Planning, 129-140, Amsterdam, 1996. IOS Press.
371. Refinement of Bayesian Networks by Combining Connectionist and Symbolic Techniques
     [Details] [PDF]
     Sowmya Ramachandran
     1995. Unpublished Ph.D. Thesis Proposal.
372. Inducing Logic Programs without Explicit Negative Examples
     [Details] [PDF]
     John M. Zelle, Cynthia A. Thompson, Mary Elaine Califf, and Raymond J. Mooney
     In Proceedings of the Fifth International Workshop on Inductive Logic Programming (ILP-95), 403-416, Leuven, Belgium, 1995.
373. Qualitative Multiple-Fault Diagnosis of Continuous Dynamic Systems Using Behavioral Modes
     [Details] [PDF]
     Siddarth Subramanian
     PhD Thesis, Department of Computer Sciences, University of Texas at Austin, Austin, TX, 1995. 128 pages. Also appears as Technical Report AI 95-239.
374. Using Inductive Logic Programming to Automate the Construction of Natural Language Parsers
     [Details] [PDF]
     John M. Zelle
     PhD Thesis, Department of Computer Sciences, The University of Texas at Austin, Austin, TX, 1995.
375. A Comparison of Two Methods Employing Inductive Logic Programming for Corpus-based Parser Constuction
     [Details] [PDF]
     John M. Zelle and Raymond J. Mooney
     In Working Notes of the IJCAI-95 Workshop on New Approaches to Learning for Natural Language Processing, 79--86, Montreal, Quebec, Canada, August 1995.
376. Multiple-Fault Diagnosis Using General Qualitative Models with Fault Modes
     [Details] [PDF]
     Siddarth Subramanian and Raymond J. Mooney
     In Working Notes of the IJCAI-95 Workshop on Engneering Problems for Qualitative Reasoning, Monreal, Quebec, August 1995.
377. Acquisition of a Lexicon from Semantic Representations of Sentences
     [Details] [PDF]
     Cynthia A. Thompson
     In Proceedings of the 33rd Annual Meeting of the Association for Computational Linguistics (ACL-95), 335-337, Cambridge, MA, 1995.
378. Induction of First-Order Decision Lists: Results on Learning the Past Tense of English Verbs
     [Details] [PDF]
     Raymond J. Mooney and Mary Elaine Califf
     Journal of Artificial Intelligence Research, 3:1-24, 1995.
379. Automated Refinement of First-Order Horn-Clause Domain Theories
     [Details] [PDF]
     Bradley L. Richards and Raymond J. Mooney
     Machine Learning, 19(2):95-131, 1995.
380. Encouraging Experimental Results on Learning CNF
     [Details] [PDF]
     Raymond J. Mooney
     Machine Learning, 19(1):79-92, 1995.
381. A Preliminary PAC Analysis of Theory Revision
     [Details] [PDF]
     Raymond J. Mooney
     In T. Petsche and S. Hanson and Jude W. Shavlik, editors, Computational Learning Theory and Natural Learning Systems, Vol. 3, 43-53, Cambridge, MA, 1995. MIT Press.
382. Automatic Student Modeling and Bug Library Construction using Theory Refinement
     [Details] [PDF]
     Paul T. Baffes
     PhD Thesis, Department of Computer Sciences, The University of Texas at Austin, Austin, TX, 1994.
383. Multiple-Fault Diagnosis Using General Qualitative Models with Fault Modes
     [Details] [PDF]
     Siddarth Subramanian and Raymond J. Mooney
     In Working Papers of the Fifth International Workshop on Principles of Diagnosis, 321-325, New Paltz, NY, October 1994.
384. Inductive Learning For Abductive Diagnosis
     [Details] [PDF]
     Cynthia A. Thompson and Raymond J. Mooney
     In Proceedings of the Twelfth National Conference on Artificial Intelligence (AAAI-94), 664-669, Seattle, WA, August 1994.
385. Comparing Methods For Refining Certainty Factor Rule-Bases
     [Details] [PDF]
     J. Jeffrey Mahoney and Raymond J. Mooney
     In Proceedings of the Eleventh International Workshop on Machine Learning (ML-94), 173--180, Rutgers, NJ, July 1994.
386. Combining Top-Down And Bottom-Up Techniques In Inductive Logic Programming
     [Details] [PDF]
     John M. Zelle, Raymond J. Mooney, and Joshua B. Konvisser
     In Proceedings of the Eleventh International Workshop on Machine Learning (ML-94), 343--351, Rutgers, NJ, July 1994.
387. Inducing Deterministic Prolog Parsers From Treebanks: A Machine Learning Approach
     [Details] [PDF]
     John M. Zelle and Raymond J. Mooney
     In Proceedings of the Twelfth National Conference on Artificial Intelligence (AAAI-94), 748--753, Seattle, WA, July 1994.
388. Learning Qualitative Models for Systems with Multiple Operating Regions
     [Details] [PDF]
     Sowmya Ramachandran, Raymond J. Mooney, and Benjamin J. Kuipers
     In Proceedings of the Eighth International Workshop on Qualitative Reasoning about Physical Systems, Nara, Japan, 1994.
389. Modifying Network Architectures For Certainty-Factor Rule-Base Revision
     [Details] [PDF]
     J. Jeffrey Mahoney and Raymond J. Mooney
     In Proceedings of the International Symposium on Integrating Knowledge and Neural Heuristics (ISIKNH-94), 75--85, Pensacola, FL, May 1994.
390. A Multistrategy Approach to Theory Refinement
     [Details] [PDF]
     Raymond J. Mooney and Dirk Ourston
     In Ryszard S. Michalski and G. Teccuci, editors, Machine Learning: A Multistrategy Approach, Vol. IV, 141-164, San Mateo, CA, 1994. Morgan Kaufmann.
391. Theory Refinement Combining Analytical and Empirical Methods
     [Details] [PDF]
     Dirk Ourston and Raymond J. Mooney
     Artificial Intelligence:311-344, 1994.
392. Integrating ILP and EBL
     [Details] [PDF]
     Raymond J. Mooney and John M. Zelle
     Sigart Bulletin (special issue on Inductive Logic Programmming), 5(1):12-21, 1994.
393. Extending Theory Refinement to M-of-N Rules
     [Details] [PDF]
     Paul T. Baffes and Raymond J. Mooney
     Informatica, 17:387-397, 1993.
394. Inductive Learning For Abductive Diagnosis
     [Details] [PDF]
     Cynthia A. Thompson
     Masters Thesis, Department of Computer Sciences, The University of Texas at Austin, Austin, TX, August 1993. 53 pages.
395. Combining FOIL and EBG to Speed-Up Logic Programs
     [Details] [PDF]
     John M. Zelle and Raymond J. Mooney
     In Proceedings of the 13th International Joint Conference on Artificial Intelligence, 1106-1111, 1993. San Francisco, CA: Morgan Kaufmann.
396. Symbolic Revision of Theories With M-of-N Rules
     [Details] [PDF]
     Paul T. Baffes and Raymond J. Mooney
     In Proceedings of the Thirteenth International Joint Conference on Artificial Intelligence (IJCAI-93), 1135-1140, Chambery, France, August 1993.
397. Learning Semantic Grammars With Constructive Inductive Logic Programming
     [Details] [PDF]
     John M. Zelle and Raymond J. Mooney
     In Proceedings of the 11th National Conference on Artificial Intelligence, 817-822, 1993. Menlo Park, CA: AAAI Press.
398. Learning to Model Students: Using Theory Refinement to Detect Misconceptions
     [Details] [PDF]
     Paul T. Baffes
     June 1993. Ph.D. proposal, Department of Computer Sciences, University of Texas at Austin.
399. Combining Connectionist and Symbolic Learning to Refine Certainty-Factor Rule-Bases
     [Details] [PDF]
     J. Jeffrey Mahoney and Raymond J. Mooney
     Connection Science:339-364, 1993.
400. Integrating Theory and Data in Category Learning
     [Details] [PDF]
     Raymond J. Mooney
     In G. V. Nakamura and D. L. Medin and R. Taraban, editors, Categorization by Humans and Machines, 189-218, 1993.
401. Learning Search-Control Heuristics for Logic Programs: Applications to Speedup Learning and Language Acquisition
     [Details] [PDF]
     John M. Zelle
     March 1993. Ph.D. proposal, Department of Computer Sciences, University of Texas at Austin.
402. Induction Over the Unexplained: Using Overly-General Domain Theories to Aid Concept Learning
     [Details] [PDF]
     Raymond J. Mooney
     Machine Learning, 10:79-110, 1993.
403. An Operator-Based Approach to First-Order Theory Revision
     [Details] [PDF]
     Bradley Lance Richards
     PhD Thesis, Department of Computer Science, University of Texas at Austin, August 1992.
404. A General Abductive system with application to plan recognition and diagnosis
     [Details] [PDF]
     Hwee Tou Ng
     PhD Thesis, Department of Computer Sciences, University of Texas at Austin, May 1992. 154 pages.
405. Schema acquisition from a single example
     [Details] [PDF]
     W. Ahn, W. F. Brewer and Raymond J. Mooney
     Journal of Experimental Psychology: Learning, Memory, and Cognition, 18:391-412, 1992.
406. Abductive Plan Recognition and Diagnosis: A Comprehensive Empirical Evaluation
     [Details] [PDF]
     Hwee Tou Ng and Raymond J. Mooney
     In Proceedings of the Third International Conference on Principles of Knowledge Representation and Reasoning, 499--508, Cambridge, MA, October 1992.
407. Speeding-up Logic Programs by Combining EBG and FOIL
     [Details] [PDF]
     John M. Zelle and Raymond J. Mooney
     In Proceedings of the 1992 Machine Learning Workshop on Knowledge Compilation and Speedup Learning, Aberdeen, Scotland, July 1992.
408. Automatic Abduction of Qualitative Models
     [Details] [PDF]
     Bradley L. Richards, Ina Kraan, and Benjamin J. Kuipers
     In Proceedings of the Fifth International Workshop on Qualitative Reasoning about Physical Systems, 295-301, 1992.
409. Using Theory Revision to Model Students and Acquire Stereotypical Errors
     [Details] [PDF]
     Paul T. Baffes and Raymond J. Mooney
     In Proceedings of the Fourteenth Annual Conference of the Cognitive Science Society, 617-622, Bloomington, IN, 1992.
410. Learning Relations by Pathfinding
     [Details] [PDF]
     Bradley L. Richards and Raymond J. Mooney
     In Proceedings of the Tenth National Conference on Artificial Intelligence (AAAI-92), 50-55, San Jose, CA, July 1992.
411. Combining Symbolic and Neural Learning to Revise Probabilistic Theories
     [Details] [PDF]
     J. Jeffrey Mahoney and Raymond J. Mooney
     In Proceedings of the ML92 Workshop on Integrated Learning in Real Domains, Aberdeen, Scotland, July 1992.
412. A First-Order Horn-Clause Abductive System and Its Use in Plan Recognition and Diagnosis
     [Details] [PDF]
     Hwee Tou Ng and Raymond J. Mooney
     June 1992. Unpublished Technical Note.
413. Growing Layers of Perceptrons: Introducing the Extentron Algorithm
     [Details] [PDF]
     Paul T. Baffes and John M. Zelle
     In Proceedings of the 1992 International Joint Conference on Neural Networks, 392--397, Baltimore, MD, June 1992.
414. Automated Debugging of Logic Programs via Theory Revision
     [Details] [PDF]
     Raymond J. Mooney and Bradley L. Richards
     In Proceedings of the Second International Workshop on Inductive Logic Programming (ILP-92), Tokyo, Japan, 1992.
415. Belief Revision in the Context of Abductive Explanation
     [Details] [PDF]
     Siddarth Subramanian
     Technical Report AI92-179, Artificial Intelligence Laboratory, University of Texas, Austin, TX, December 1992.
416. Batch versus Incremental Theory Refinement
     [Details] [PDF]
     Raymond J. Mooney
     In Proceedings of the 1992 AAAI Spring Symposium on Knowledge Assimilation, Standford, CA, March 1992.
417. Using Explanation-Based and Empirical Methods in Theory Revision
     [Details] [PDF]
     Dirk Ourston
     PhD Thesis, Department of Computer Science, University of Texas at Austin, 1991.
418. First-Order Theory Revision
     [Details] [PDF]
     Bradley L. Richards and Raymond J. Mooney
     In Proceedings of the Eighth International Machine Learning Workshop, pp. 447-451, Evanston, IL, June 1991.
419. Symbolic and Neural Learning Algorithms: An Experimental Comparison
     [Details] [PDF]
     J.W. Shavlik, Raymond J. Mooney and G. Towell
     Machine Learning, 6:111-143, 1991. Reprinted in {it Readings in Knowledge Acquisition and Learning}, Bruce G. Buchanan and David C. Wilkins (eds.), Morgan Kaufman, San Mateo, CA, 1993..
420. An Efficient First-Order Horn-Clause Abduction System Based on the ATMS
     [Details] [PDF]
     Hwee Tou Ng and Raymond J. Mooney
     In Proceedings of the Ninth National Conference on Artificial Intelligence (AAAI-91), 494-499, Anaheim, CA, July 1991.
421. Improving Shared Rules in Multiple Category Domain Theories
     [Details] [PDF]
     Dirk Ourston and Raymond J. Mooney
     In Proceedings of the Eighth International Workshop on Machine Learning, 534-538, Evanston, IL, June 1991.
422. Constructive Induction in Theory Refinement
     [Details] [PDF]
     Raymond J. Mooney and Dirk Ourston
     In Proceedings of the Eighth International Workshop on Machine Learning, 178-182, Evanston, IL, June 1991.
423. Theory Refinement with Noisy Data
     [Details] [PDF]
     Raymond J. Mooney and Dirk Ourston
     Technical Report AI91-153, Artificial Intelligence Laboratory, University of Texas, Austin, TX, March 1991.
424. Changing the Rules: A Comprehensive Approach to Theory Refinement
     [Details] [PDF]
     D. Ourston and Raymond J. Mooney
     In Proceedings of the Eighth National Conference on Artificial Intelligence (AAAI-90), 815-820, Boston, MA, July 1990.
425. On the Role of Coherence in Abductive Explanation
     [Details] [PDF]
     Hwee Tou Ng and Raymond J. Mooney
     In Proceedings of the Eighth National Conference on Artificial Intelligence (AAAI-90), 337--342, Boston, MA, July 1990.
426. Learning Plan Schemata From Observation: Explanation-Based Learning for Plan Recognition
     [Details] [PDF]
     Raymond J. Mooney
     Cognitive Science, 14(4):483-509, 1990.
427. Processing Issues in Comparisons of Symbolic and Connectionist Learning Systems
     [Details] [PDF]
     Douglas Fisher and Kathleen McKusick and Raymond J. Mooney and Jude W. Shavlik and Geoffrey Towell
     In Proceedings of the Sixth International Workshop on Machine Learning, 169--173, Ithaca, New York, 1989.
428. An Experimental Comparison of Symbolic and Connectionist Learning Algorithms
     [Details] [PDF]
     Raymond J. Mooney, J.W. Shavlik, G. Towell and A. Gove
     In Proceedings of the Eleventh International Joint Conference on Artificial Intelligence (IJCAI-89), 775-780, Detroit, MI, August 1989. Reprinted in ``Readings in Machine Learning'', Jude W. Shavlik and T. G. Dietterich (eds.), Morgan Kaufman, San Mateo, CA, 1990..
429. The Effect of Rule Use on the Utility of Explanation-Based Learning
     [Details] [PDF]
     Raymond J. Mooney
     In Proceedings of the 11th International Joint Conference on Artificial Intelligence, 725-730, 1989. San Francisco, CA: Morgan Kaufmann.
430. Generalizing the Order of Operators in Macro-Operators
     [Details] [PDF]
     Raymond J. Mooney
     In Proceedings of the Fifth International Conference on Machine Learning (ICML-88), 270-283, Ann Arbor, MI, June 1988.
431. A General Explanation-Based Learning Mechanism and its Application to Narrative Understanding
     [Details] [PDF]
     Raymond J. Mooney
     Ph.D. thesis, Department of Computer Science, University of Illinois at Urbana-Champaign, 1988
432. Integrated Learning of Words and their Underlying Concepts
     [Details] [PDF]
     Raymond J. Mooney
     In Proceedings of the Ninth Annual Conference of the Cognitive Science Society, 947-978, Seattle, WA, July 1987.
433. Schema Acquisition from One Example: Psychological Evidence for Explanation-Based Learning
     [Details] [PDF]
     W. Ahn, Raymond J. Mooney, W.F. Brewer and G.F. DeJong
     In Proceedings of the Ninth Annual Conference of the Cognitive Science Society, 50-57, Seattle, WA, July 1987.
434. A Domain Independent Explanation-Based Generalizer
     [Details] [PDF]
     Raymond J. Mooney and S.W. Bennett
     In Proceedings of the Fifth National Conference on Artificial Intelligence (AAAI-86), 551-555, Philadelphia, PA, August 1986.
435. Explanation-Based Learning: An Alternative View
     [Details] [PDF]
     G.F. DeJong and Raymond J. Mooney
     Machine Learning:145-176, 1986.
436. Generalizing Explanations of Narratives into Schemata
     [Details] [PDF]
     Raymond J. Mooney
     In Proceedings of the Third International Machine Learning Workshop, 126--128, New Brunswick, New Jersey, 1985.
437. Learning Schemata for Natural Language Processing
     [Details] [PDF]
     Raymond J. Mooney and Gerald F. DeJong
     In Proceedings of the Ninth International Joint Conference on Artificial Intelligence (IJCAI-85), 681-687, Los Angeles, CA, August 1985.
438. Generalizing Explanations of Narratives into Schemata
     [Details] [PDF]
     Raymond J. Mooney
     Masters Thesis, Department of Computer Science, University of Illinois at Urbana-Champaign, 1985.