Mooney, Raymond J. - Department of Computer Sciences, University of Texas at Austin

• Proceedings of the 19th International Conference on Machine Learning (ICML2002), pp. 1926, Sydney, Australia, July 2002
• Appears in Proceedings of the 12th European Conference on Machine Learning, pp. 466477, Freiburg, Germany, September 2001
• Oxford Handbook of Computational Linguistics, R. Mitkov (Ed.), Oxford University Press, pp. 376394, 2003
• Lap Poon Rupert Tang The Dissertation Committee for Lap Poon Rupert Tang
• Ph.D. Proposal, Department of Computer Sciences, University of Texas at Austin, September 1996 Also appears as Technical Report AI 96250, Artificial Intelligence Lab, University of Texas at Austin
• Un Yong Nahm The Dissertation Committee for Un Yong Nahm
• Unpublished Technical Note, March 2002. Extracting Gene and Protein Names from Biomedical Abstracts
• Ph.D. Proposal, Department of Computer Sciences, University of Texas at Austin, May 2000
• Appears in Proceedings of the Seventh International Converence on Knowledge Discovery and Data Mining (KDD2001), pp.233238, San Francisco, CA, August 2001
• Appears in Proceedings of the SIGIR2001 Workshop on Recommender Systems, New Orleans, LA, September 2001
• Ph.D. proposal, Department of Computer Sciences, University of Texas at Austin, June 1993. Also appears as Technical Report AI 94215, Artificial Intelligence Laboratory,
• ELIXIR: A library for writing wrappers in Java Edward Wild
• Ph.D. proposal, Department of Computer Sciences, University of Texas at Austin, March 1993
• Appears in Proceedings of the KDD(Knowledge Discovery in Databases)2000 Workshop on Text Mining, pp.5158, Boston, MA, August 2000
• Proceedings of the 21st International Conference on Machine Learning, (ICML2004), pp. 584591, Banff, Canada, July, 2004
• Technical Report, Artificial Intelligence Lab, University of Texas at Austin, January 1996.
• Appears in Proceedings of the NAACL Workshop on WordNet and Other Lexcical Resources: Applications, Extensions and Customizations, pp.144149, Pittsburg, PA, June 2001
• Proceedings of the KDD2003 Workshop on MultiRelational Data Mining (MRDM2003), pp.107121, Washington DC, August, 2003
• Appears in Proceedings of the Joint SIGDAT Conference on Empirical Methods in Natural Language Processing and Very Large Corpora (EMNLP/VLC2000), pp.133141, Hong Kong, October, 2000
• Ph.D. Proposal, Department of Computer Sciences, University of Texas at Austin, February 1996.
• Proceedings of the 42nd Annual Meeting of the Association for Computational Linguistics (ACL2004) pp. 439446, Barcelona, Spain, July 2004.
• Ph.D. Proposal, Department of the Computer Sciences, University of Texas at Austin, February 2001
• Appears inInductive Logic Programming: Selected Papers from the 6th International Workshop S. Muggleton (Ed.), pp.322, Springer Verlag, Berlin, 1997.
• Unpublished Technical Note, January 1997 Parameter Revision Techniques for Bayesian Networks
• Appears in Proceedings of the Eighth International Machine Learning Workshop, pp. 178182, Evanston, IL, June 1991.
• Appears in New Generation Computing, 16, 3, p. 263281 (1998) Advantages of Decision Lists and Implicit Negatives in
• Appears in Proceedings of the Eighth International Machine Learning Workshop, pp. 534538, Evanston, IL, June 1991.
• Appears in Working Papers of the 5th International Workshop on Principles of Diagnosis pp.321325, New Paltz, NY, October 1994
• AAAI-2002 Spring Symposium on Mining Answers from Texts and Knowledge Bases, March 2002 1 Text Mining with Information Extraction
• Appears in Proceedings of the Sixteenth National Conference on Artificial Intelligence (AAAI99), pp. 328334, Orlando, FL, July 1999
• Ph.D. Proposal, Department of Computer Sciences, University of Texas at Austin, October 1995.
• Appears in Machine Learning, 19, 2, pp.95-131, 1995 Machine Learning, ??, 1 39 ??
• Appears in Symbolic, Connectionist, and Statistical Approaches to Learning for Natural Language Processing, Springer Verlag, 1996
• Appears in Symbolic, Connectionist, and Statistical Approaches to Learning for Natural Language Processing, Springer Verlag, 1996.
• Proceedings of the AAAI-2004 Workshop on Adaptive Text Extraction and Mining (ATEM-2004), pp. 27-32, San Jose, CA, July 2004.
• Proceedings of the Twentieth National Conference on Artificial Intelligence (AAAI-05), pp. 1062--1068, Pittsburgh, PA, July 2005.
• Utilizing HTML Structure and Linked Pages to Improve Learning for Text Categorization
• Appears in Proceedings of the Fifth International Workshop on Inductive Logic Programming (ILP-95), pp.403-416, Leuven, Belgium, September 1995
• Appears in Proceedings of the ICML-97 Workshop on Automata Induction, Grammatical Inference, and Language Aquicision, Nashville, TN, July 1997
• In Proceedings of the 45th Annual Meeting of the Association for Computational Linguistics (ACL-07). pp. 960-967, Prague, Czech Republic, June 2007. Learning Synchronous Grammars for Semantic Parsing with
• Appears in Proceedings of The 16th European Conference on Machine Learning (ECML), Porto, Portugal, pp. 268-279, October 2005.
• Proceedings of the Ninth AAAI/SIGART Doctoral Consortium, pp. 981-982, San Jose, CA, July 2004
• In Proceedings of the 19th International FLAIRS Conference (FLAIRS-2006). pp. 580-585, Melbourne Beach, FL, May 2006. Using Active Relocation to Aid Reinforcement Learning
• Appears in Conference on Empirical Methods in Natural Language Processing(EMNLP-96) pp. 82-91, Philadelphia, PA, May 1996
• Appears in Proceedings of the Thirteenth National Conference on Artificial Intelligence (AAA pp. 1050-1055, Portland, OR, August 1996
• In Proceedings of the 22nd Conference on Artificial Intelligence (AAAI-07). pp. 608-614, Vancouver, Canada, July 2007. Mapping and Revising Markov Logic Networks for Transfer Learning
• Appears in Abduction and Induction P. Flach and A. Kakas (Eds.), pp.181-191, Kluwer Academic Publishers, 2000
• To appear in Proceedings of the 24th Annual Intl. Conf. on Machine Learning (ICML-2007). Corvallis, OR, June 2007. Multiple Instance Learning for Sparse Positive Bags
• Appears in Proceedings of the Association for Computational Linguistics (ACL-97) pp. 482-489, July 1997
• Appears in Proceedings of the 5th International Conference on Data Mining (ICDM-2005) pp. 58-65, Houston, TX, November 2005
• In Proceedings of the Human Language Technology Conference of the North American Chapter of the Association for Computational Linguistics (NAACL/HLT-07). pp. 172-179, Rochester, NY, April 2007.
• Proceedings of the IBM Austin Center for Advanced Studies 5th Annual Austin CAS Conference, Austin, TX, February 2004
• PhD Proposal, Nov 2003 (Also appears as Technical Report, UT-AI-TR-03-306) Creating Diverse Ensemble Classifiers
• Prem Noel Melville The Dissertation Committee for Prem Noel Melville
• Appears in Proceedings of the Twelfth National Conference on Artificial Intelligence (AAAI-94), pp. 664-669, Seattle, WA, July, 1994
• Sonal Gupta Activity Retrieval in Closed Captioned Videos
• Appears in Computational Learning Theory and Natural Learning Systems, Vol. 3, T. Petsche, S. Judd, and S. Hanson (Eds.), pp.43-53, MIT Press, 1995
• Appears in Proceedings of the Twelfth National Conference on Artificial Intelligence (AAAI-94), pp. 748-753, Seattle, WA, July, 1994
• Appears in Proceedings of the Eleventh National Conference of the American Association for Artificial Intelligence (AAAI-93), pp.817-822, Washington, D.C. July, 1993
• Lilyana Simeonova Mihalkova The Dissertation Committee for Lilyana Simeonova Mihalkova
• In Proceedings of the European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases, Part 2, pp. 111-127, Bled, Slovenia, September 2009.
• In Proceedings of the International Workshop on Statistical Relational Learning (SRL-09), Leuven, Belgium, July 2009. Max-Margin Weight Learning for
• In Proceedings of the 19th International Conference on Inductive Logic Programming (ILP-09), Leuven, Belgium, July 2009. Speeding up Inference in Statistical Relational Learning
• Undergraduate Honor Thesis, May 2004. Explanation for Recommender Systems
• In Proceedings of the IJCAI-09 Workshop on Plan, Activity, and Intent Recognition (PAIR-09), Pasadena, CA, July 2009. Probabilistic Abduction using Markov Logic Networks
• In Proceedings of the 21st International Joint Conference on Artificial Intelligence (IJCAI-09), pp. 1163--1168, Pasadena, CA, July 2009. Transfer Learning from Minimal Target Data
• Search Query Disambiguation from Short Sessions Lilyana Mihalkova and Raymond Mooney
• In Proceedings of the 25th International Conference on Machine Learning (ICML),. Helsinki, Finland, July 2008. Discriminative Structure and Parameter Learning for
• In Proceedings of the AAAI-08 Workshop on Transfer Learning For Complex Tasks,. Chicago, IL, July 2008. Transfer Learning by Mapping with Minimal Target Data
• In Proceedings of the 23rd AAAI Conference on Artificial Intelligence (AAAI), Senior Member Paper,. pp. 1598-1601, Chicago, IL, July 2008. Learning to Connect Language and Perception
• Yuk Wah Wong The Dissertation Committee for Yuk Wah Wong
• Improving Learning of Markov Logic Networks using Transfer and Bottom-Up Induction
• In Proceedings of the Sixth IEEE International Conference on Data Mining (ICDM-06). pp. 87-96, Hong Kong, December 2006. Adaptive Blocking: Learning to Scale Up Record Linkage
• In Proceedings of the 3rd IEEE International Conference on Autonomic Computing (ICAC-2006), Poster Session. Dublin, Ireland, June 2006. Fast and Effective Worm Fingerprinting via
• In Proceedings of the 2006 AAAI Fellows Symposium. Boston, MA, July 2006. Learning Language from Perceptual Context: A Challenge Problem for AI
• In Proceedings of the Joint 21st International Conference on Computational Linguistics and 44th Annual Meeting of the Association for Computational Linguistics (COLING/ACL 2006), pp. 913-920, Sydney, Australia, July 2006.
• In Proceedings of the COLING/ACL-2006 Main Conference Poster Sessions. pp. 263-270, Sydney, Australia, July 2006. Discriminative Reranking for Semantic Parsing
• In Proceedings of the Human Language Technology Conference of the North American Chapter of the Association for Computational Linguistics (HLT/NAACL-2006). pp. 439-446, New York City, NY, June 2006.
• Also appears as Technical Report UT-AI-TR-06-327, Artificial Intelligence Lab, University of Texas at Austin, February 2006. Learning Semantic Parsers
• Also appears as Technical Report UT-AI-05-326, Artificial Intelligence Lab, University of Texas at Austin, November 2005 A Kernel-based Approach to Learning Semantic Parsers
• Also appears as Technical Report UT-AI-05-323, Artificial Intelligence Lab, University of Texas at Austin, October 2005. Learning for Semantic Parsing Using Statistical Machine
• Appears in Proceedings of the 2005 Dagstuhl Seminar on Machine Learning for the Semantic Web, Dagstuhl, Germany, February 2005.
• Appears in Proceedings of the Human Language Technology Conference and Conference on Empirical Methods in Natural Language Processing
• Mining Knowledge from Text Using Information Extraction Raymond J. Mooney and Razvan Bunescu
• To Appear in Statistical Relational Learning Lise Getoor and Ben Taskar (Eds.) forthcoming book, 2005
• To Appear in The Second International Conference on Autonomic Computing Towards Self-Configuring Hardware for Distributed Computer Systems
• Multilingualism and Electronic Language Management: Proceedings of the 4th International MIDP Colloquium, September 2003, Bloemfontein, South Africa, Daelemans, W., du Plessis, T., Snyman, C. and Teck, L. (Eds.)
• Active Feature-Value Acquisition for Classifier Induction Prem Melville
• Proceedings of the 4th IEEE International Conference on Data Mining, (ICDM-2004), Brighton, UK, November, 2004
• Proceedings of the Tenth ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD-2004), pp. 59-68, Seattle, WA, August 2004.
• Proceedings of the AAAI-2004 Workshop on Supervisory Control of Learning and Adaptive Systems, pp. 30-35, San Jose, CA, July 2004.
• Proceedings of the Ninth AAAI/SIGART Doctoral Consortium, pp. 979-980, San Jose, CA, July 2004
• Proceedings of the ICML-2004 Workshop on Statistical Relational Learning and its Connections to Other Fields (SRL-2004), Banff, Canada, July 2004
• Proceedings of the SIAM International Conference on Data Mining, (SDM-2004), pp. 333-344, Lake Buena Vista, FL, April, 2004
• Proceedings of the Eighteenth National Conference on Artificial Intelligence(AAAI-2002), pp. 187-192, Edmonton, Canada, July 2002
• Creating Diversity In Ensembles Using Artificial Data
• Comparative experiments on learning information extractors for proteins and their interactions
• PhD Proposal, Oct 2003 (Also appears as Technical Report, UT-AI-TR-03-305) Learnable Similarity Functions and
• Proceedings of the KDD-2003 Workshop on Data Cleaning, Record Linkage, and Object Consolidation,pp. 7-12, Washington DC, August, 2003
• Proceedings of the Ninth ACM SIGKDD International Conference on Knowledge Discovery and Data Mining(KDD-2003), Washington DC, pp.39-48, August, 2003
• Proceedings of ICML-2003 Workshop on Machine Learning in Bioinformatics, pp. 46-53, Washington, DC, August 2003
• Proceedings of the ICML-2003 Workshop on the Continuum from Labeled to Unlabeled Data in Machine Learning and Data Mining Systems, pp.42-49, Washington DC, August, 2003
• Journal of Machine Learning Research 4 (2003) 177-210 Submitted 12/01; Revised 2/03; Published 6/03 Bottom-Up Relational Learning of Pattern Matching Rules for
• Journal of Artificial Intelligence Research 18 (2003) 1-44 Submitted 5/02; published 1/03 Acquiring Word-Meaning Mappings
• Noppadon Kamolvilassatian Property-Based Feature Engineering and Selection
• In Proceedings of the ACL-IJCNLP 2009, pp. 611--619, Suntec, Singapore, August 2009. Learning a Compositional Semantic Parser
• Appears in the Proceedings of the National Science Foundation Workshop on Next Generation Data Mining, Nov. 2002, Baltimore, MD. Relational Data Mining with Inductive Logic Programming for Link Discovery
• To appear in Proceedings of the 24th Annual Intl. Conf. on Machine Learning (ICML-07). Corvallis, OR, June 2007. Bottom-Up Learning of Markov Logic Network Structure
• Proceedings of the Seventeenth International Joint Conference on Artificial Intelligence(IJCAI-01),pages 979-984, Seattle, WA, August, 2001 Mining Soft-Matching Rules from Textual Data
• In the Proceedings of the Seventeenth National Conference on Artificial Intelligence(AAAI-2000),pp.627-632,Austin, TX, 20001 A Mutually Beneficial Integration of
• Appears in Proceedings of the Fifth ACM Conference on Digital Libraries, pp.195-240, San Antonio, TX, June 2000
• Appears in Proceedings of the SIGIR-99 Workshop on Recommender Systems: Algorithms and Evaluation, Berkeley, CA, August 1999
• Appears in: Proceedings of the Sixteenth National Conference on Artificial Intelligence (AAAI-99) Automatic Construction of Semantic Lexicons for Learning
• Appears in Workshop Notes for the Workshop on Learning Language in Logic, Bled, Slovenia, pp. 7-14, June 1999 Also appears in Learning Language in Logic, J. Cussens and S. Dzeroski (Eds.), pp. 57-66, Springer Verlag, Berlin
• Sowmya Ramachandran Theory Re nement of Bayesian Networks with Hidden Variables
• Technical Report AI-98-271, Artificial Intelligence Lab, University of Texas at Austin, May 1998
• Using Multi-Strategy Learning to Improve Planning E ciency and Quality
• Appears in Proceedings of AAAI Spring Symposium on Applying Machine Learning to Discourse Processing, pp. 6-11, March, 1998
• Appears in the Working Notes of the IJCAI-97 Workshop on Abduction and Induction in AI, pp.37-42, Nagoya, Japan, August 1997
• Ph.D. Proposal, Department of Computer Sciences, University of Texas at Austin, 1997
• Appears in Proceedings of the Fifteenth International Joint Conference on Artificial Intelligence (IJCAI-97), pp.1227-1232, Nagoya, Japan, August 1997
• Ulf Hermjakob Learning Parse and Translation Decisions
• Unpublished Technical Note An Inductive Logic Programming Method for
• Conclusions ASSERT demonstrates how theory refinement techniques
• Appears in Proceedings of the Thirteenth National Conference on Artificial Intelligence (AAAI-96), pp. 843-848, Portland, OR, August 1996.
• Using Theory Revision to Model Students and Acquire Stereotypical Errors 3
• Appears in Proceedings of the 1996 IEEE International Conference on Neural Networks, pp.82-87, Washington D.C., June 1996.
• Appears in New Directions in AI Planning, IOS Press, 1996, pp. 129-140 Also appears in Proceedings of the Third European Workshop on Planning, 1995.
• Siddarth Subramanian Qualitative Multiple-Fault Diagnosis of Continuous Dynamic
• AUTOMATIC STUDENT MODELING AND BUG LIBRARY CONSTRUCTION USING THEORY REFINEMENT
• Appears in The Intl Symposium on Integrating Knowledge and Neural Heuristics (ISIKNH-94), pp. 75-85, Pensacola, FL, May, 1994
• Appears in Machine Learning: A Multistrategy Appraoch, Vol. IV R.S. Michalski & G. Teccuci (Eds.), pp.141-164, Morgan Kaufman, San Mateo, CA, 1994
• Appears in Informatica, 17, pp. 387-397, 1993 Informatica 17 page xxx yyy 1
• Appears in Proceedings of the Thirteenth International Joint Conference on Artificial Intellige (IJCAI-93), pp.1106-1111, Chambery, France, 1993
• Appears in Proceedings of the Thirteenth International Joint Conference on Artificial Intellige pp.1135-1140, Chambery, France, 1993
• Appears in Connection Science, 5, pp.339-364, 1993 (Special issue on Architectures for Integrating Neural and Symbolic Processing)
• Appears in Categorization by Humans and Machines: The Psychology of Learning and Motivation, Vol. 29, G. Nakamura, R. Taraban & D.L. Medin (Eds.), pp.189-218, Academic Press, Orlando, FL, 1993
• Appears in Proceedings of the Tenth National Conference on Artificial Intelligence (AAAI-92), pp.723-728, San Jose, CA, July, 1992
• Appears in Proceedings of the Tenth National Conference on Artificial Intelligence (AAAI-92), pp.50-55, San Jose, CA, July, 1992
• Unpublished Technical Note A First-Order Horn-Clause Abductive System
• Growing Layers of Perceptrons: Introducing the Extentron Algorithm
• Ph.D. proposal, Department of Computer Sciences, University of Texas at Austin, 1992 Also appears as Technical Report AI 92-179, Artificial Intelligence Lab, University of Texas at Austin, March, 1991
• Appears in Proceedings of the 1992 AAAI Spring Symposium on Knowledge Assimilation, Standford, CA, March, 1992
• Appears in Proceedings of the Ninth National Conference on Artificial Intelligence (AAAI-91), pp. 494-499, Anaheim, CA, July, 1991
• Proceedings of the 21st International Conference on Machine Learning, (ICML-2004), pp. 81-88, Banff, Canada, July, 2004
• Appears in Proceedings of the Eighth National Conference on Artificial Intelligence (AAAI-90), pp.337-342, Boston, MA, July, 1990
• John M. Zelle Using Inductive Logic Programming to Automate the
• Appears in Proceedings of the 3rd International Conference on Principles of Knowledge Representation and Reasoning, pp. 499-508, Cambridge, MA, October, 1992
• Computational Linguistics and Intelligent Text Processing: Proceedings of the 8th International Conference, CICLing 2007, Mexico City (invited paper), A. Gelbukh (Ed.), pp. 311-324, Springer, Berlin, Germany, February 2007.
• In Proceedings of the 25th International Conference on Machine Learning (ICML),. Helsinki, Finland, July 2008. Learning to Sportscast: A Test of Grounded Language Acquisition
• Text Categorization Through Probabilistic Learning: Applications to Recommender Systems
• 16 1094-7167/03/$17.00 2003 IEEE IEEE INTELLIGENT SYSTEMS Published by the IEEE Computer Society
• Appears in SIGART Bulletin, Volume 5, Number 1, pp. 12-21, Jan, 1994 Integrating ILP and EBL
• Proceedings of the IJCAI-2003 Workshop on Information Integration on the Web, pp. 67-72, Acapulco, Mexico, August, 2003
• COGNITIVE SCIENCE 14, 488509 (1990) LearningPlanSchemataFromObservation
• Technical Report AI 91-153, Artificial Intelligence Lab, University of Texas at Austin, March, 1991 Theory Re nement with Noisy Data3
• Appears in Proceedings of the Second International Workshop on Inductive Logic Programming, Tokyo, Japan, June, 1992
• Artificial Intelligence 66 (1994) 273-309 273 ARTINT 1071
• Appears in Proceedings of 8th International Qualitative Reasoning Workshop (QR-94) pp.213-223, Nara, Japan, June 1994
• Appears in Proceedings of the Eleventh International Workshop on Machine Learning pp. 343-351, Rutgers, NJ, July, 1994
• Appears in Proceedings of the Eleventh International Workshop on Machine Learning pp. 173-180, Rutgers, NJ, July, 1994
• Appears in Proceedings of the 33rd Annual Meeting of the Association for Computational Linguistics (ACL-95), pp.325-337, Boston, MA, July 1995
• Appears in Working Notes of the IJCAI-95 Workshop on Engineering Problems for Qualitative Reasoning, Monreal, Quebec, Canada, August 1995
• Advances in Neural Information Processing Systems, Vol. 18: Proceedings of the 2005 Conference (NIPS) Y. Weiss, B. Schoelkopf, J. Platt (Eds.), MIT Press, 2006.
• REFINEMENT BASED STUDENT M ODELING Towell, G. G., Shavlik, J. W., and Noordewier, M. O. (1990). Refinement of approximate
• Appears in Proceedings of the Third International Workshop on Multi-Strategy Learning (MSL-96) pp. 271-279, Harpers Ferry, WV, May 1996
• Combining Symbolic and Connectionist Learning Methods to Re ne Certainty-Factor Rule-Bases
• Appears in Working Papers of the ACL-97 Workshop on Natural Language Learning, pp. 9-15, Madrid, Spain, July 1997
• Appears in Working Notes of the IJCAI-97 Workshop on Frontiers of Inductive Logic Programming, pp.7-11, Nagoya, Japan, August 1997
• Appears in Proceedings of the Fifteenth International Conference on Machine Learning pp. 454-462, Madison, WI, July 1998
• In Semi-Supervised Learning, O. Chapelle, B. Schoelkopf, and A. Zien (eds.), MIT Press, 2006, to appear. 3 Probabilistic Semi-Supervised Clustering
• Semantic Lexicon Acquisition for Learning Natural Language Interfaces
• Appears in Proceedings of the Sixteenth International Machine Learning Conference, pp.406-414, Bled, Slovenia, June 1999
• Proceedings of the IJCAI-2003, pp.505-510, Acapulco, Mexico, August 2003
• In Proceedings of the HLT-NAACL Workshop on Linking Natural Language Processing and Biology: Towards deeper biological literature analysis (BioNLP-2006). pp. 49-56, New York City, NY, June 2006.
• Journal of Arti cial Intelligence Research 3 1995 1-24 Submitted 1 95; published 6 95 Induction of First-Order Decision Lists
• Appears in IJCAI 95 Workshop on New Approaches to Learning for Natural Language Processing, pp.79-86, Motreal, Quebec, Canada, August 1995
• Appears in Proceedings of the Sixth Workshop on Very Large Corpora, pp. 57-65, August, 1998 Semantic Lexicon Acquisition for Learning
• Technical Report AI-06-335, Artificial Intelligence Lab, The University of Texas at Austin, August 2006. Fast and Effective Worm Fingerprinting via Machine Learning
• Unpublished Technical Note, January 1997 Semantic Lexicon Acquisition
• Proceedings of the Eleventh ACM SIGKDD International Conference on Knowledge Discovery and Data Mining Chicago, IL, pp. 532--537, August 2005.
• Machine Learning, 6, 111-143 (1991) 1991Kluwer Academic Publishers, Boston. Manufactured in The Netherlands.
• Appears in Proceedings of The 16th European Conference on Machine Learning (ECML), Porto, Portugal, pp. 741-749, Oct 2005.
• Proceedings of the 21st National Conf. on Artificial Intelligence (AAAI '06), July 1620, 2006, Boston, MA. 1 Walk the Talk
• Watch, Listen & Learn: Co-training on Captioned Images and Videos
• The Role of Embodied Intention in Early Lexical Acquisition
• Appears in Proceedings of the Thirteenth National Conference on Artificial Intelligence (AAAI-96) pp. 965-970, Portland, OR, August 1996
• Mikhail Yuryevich Bilenko The Dissertation Committee for Mikhail Yuryevich Bilenko
• Proceedings of the CIKM-2002 (short paper), pp.681-683, McLean, VA, November 2002
• In Proceedings of the 45th Annual Meeting of the Association for Computational Linguistics (ACL-2007). pp. 576-583, Prague, Czech Republic, June 2007. Learning to Extract Relations from the Web
• Relational Learning Techniques for Natural Language Information Mary Elaine Cali
• Proceedings of the EACL-2003 Workshop on the Computational Treatment of Anaphora, pp. 47-52, Budapest, Hungary, April 2003.
• Proceedings of the ICML-2002 Workshop on Text Learning, pp. 18-27, Sydney, Australia, July 2002
• Machine Learning, 10, 79-110 (1993) 1993 Kluwer Academic Publishers, Boston. Manufactured in The Netherlands.
• PhD Proposal, Oct 2004 (Also Appears as Technical Report TR-05-02), Learning for Collective Information Extraction
• Appears in Proceedings of the 1992 Machine Learning Workshop on Knowledge Compilation and Speedup Learning, Aberdeen, Scotland, July, 1992
• In Proceedings of the Human Language Technology Conference of the North American Chapter of the Association for Computational Linguistics, Short Papers (NAACL/HLT-2007), pp. 81-84, Rochester, NY, April 2007.
• To Appear in Proceedings of the ICML-2004 Workshop on Statistical Relational Learning and its Connections to Other Fields (SRL-2004), Banff, Canada, July 2004
• Proceedings of 5th International Workshop on Multiple Classifier Systems (MCS-2004), LNCS Vol. 3077, pp. 293-302, Cagliari, Italy, Springer Verlag, June 2004.
• Unpublished Technical Note, Apr 2004 Learning Transformation Rules for Semantic Parsing
• Appears in Proceedings of AAAI-98/ICML-98 Workshop on Learning for Text Categorization and the AAAI-98 Workshop on Recommender Systems,pp.49-54 and pp.70-74, Madison, WI, July 1998
• In Data Mining: Next Generation Challenges and Future Directions, H. Kargupta, A. Joshi, K. Sivakumar, and Y. Yesha (Eds.), AAAI Press, 2004
• Papers from the AAAI 2004 Spring Symposium on Language Learning: An Interdisciplinary Perspective, pp. 39-44, Stanford, CA, March 2004.
• Explaining Recommendations: Satisfaction vs. Promotion Mustafa Bilgic
• In Proceedings of the ACL-ISMB Workshop on Linking Biological Literature, Ontologies and Databases: Mining Biological Semantics pp. 46--53, Detroit, MI, June 2005.
• To Appear in Proceedings of the KDD-05 Workshop on Utility-Based Data Mining, Chicago, IL, August 2005.
• In Proceedings of the Ninth Conference on Computational Natural Language Learning Ann Arbor, MI, pp. 9--16, June 2005.
• Sugato Basu The Dissertation Committee for Sugato Basu
• To Appear in Proceedings of the 5th International Conference on Data Mining (ICDM-2005) An Expected Utility Approach to Active Feature-value Acquisition
• In Proceedings of the 11th Conference of the European Chapter of the Association for Computational Linguistics (EACL-06). pp. 9-16, Trento, Italy, April 2006.
• In Proceedings of the 22nd Conference on Artificial Intelligence (AAAI-07). pp. 895-900, Vancouver, Canada, July 2007. Learning Language Semantics from Ambiguous Supervision
• Rohit Jaivant Kate The Dissertation Committee for Rohit Jaivant Kate
• In Proceedings of the European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases, Part 1, pp. 564-579, Bled, Slovenia, September 2009.
• Appears in Proceedings of the 1992 Machine Learning Workshop on Integrated Learning in Real Domains, Aberdeen, Scotland, July, 1992
• PhD Proposal, Nov 2003 (Also Appears as Technical Report, UT-AI-TR-03-307) Semi-supervised Clustering: Learning with Limited User Feedback
• Machine Learning, 19,79-92 (1995) (c) 1995 KluwerAcademic Publishers, Boston. Manufactured in The Netherlands.