Department of Computer Science

Machine Learning Research Group

University of Texas at Austin Artificial Intelligence Lab

Publications: 2009

  1. Learning Language from Perceptual Context
    [Details] [PDF] [Slides]
    David L. Chen
    December 2009. Ph.D. proposal, Department of Computer Sciences, University of Texas at Austin.
  2. Discriminative Learning with Markov Logic Networks
    [Details] [PDF] [Slides]
    Tuyen N. Huynh
    October 2009. Ph.D. proposal, Department of Computer Sciences, University of Texas at Austin.
  3. 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.
  4. 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.
  5. 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.
  6. Max-Margin Weight Learning for Markov Logic Networks
    [Details] [PDF] [Slides]
    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.
  7. 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.
  8. 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.
  9. 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.
  10. Learning a Compositional Semantic Parser using an Existing Syntactic Parser
    [Details] [PDF] [Slides]
    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.
  11. Probabilistic Abduction using Markov Logic Networks
    [Details] [PDF] [Slides]
    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.
  12. 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.
  13. 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.
  14. 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.