Members - Faculty, students, and collaborators |
Research - Details about our current research projects |
Publications - Recent technical papers and presentations |
2008
McGovern, Amy and Jensen, David (2008) Optimistic Pruning for Multiple Instance Learning. Pattern Recognition Letters. Volume 29, Issue 9, pages 1252-1260. [pdf (224K, submitted version. The final version is online here.)]
McGovern, Amy and Utz, Christopher M. and Walden, Susan E. and Trytten, Deborah A. and Shehab, Randa L. (2008) Learning the Structure of Retention Data using Bayesian Networks. To appear in the 2008 Frontiers in Education Conference.
Hiers, Nathan; McGovern, Amy; Rosendahl, Derek H.; Brown, Rodger A; Droegemeier, Kelvin K. (2008). Using Spatiotemporal Relational Data Mining to Identify the Key Parameters for Anticipating Rotation Initiation in Simulated Supercell Thunderstorms. Preprints of the Sixth Conference on Artificial Intelligence and its Applications to the Environmental Sciences, joint session with the 24th Conference on International Interactive Information and Processing Systems (IIPS) for Meteorology, Oceanography, and Hydrology. [pdf 1.1M]
Gagne II, David John; McGovern, Amy and Brotzge, Jerry. (2008) Automated Classification of Convective Areas in Reflectivity using Decision Trees. Preprints of the Sixth Conference on Artificial Intelligence and its Applications to the Environmental Sciences, joint session with the 19th Conference on Probability and Statistics in the Atmospheric Sciences. [pdf 556K]
Gagne II, David John; McGovern, Amy and Brotzge, Jerry. (2008) Using Multiple Machine Learning Techniques to Improve the Classification of a Storm Set. Preprints of the Sixth Conference on Artificial Intelligence and its Applications to the Environmental Sciences. [pdf 40K]
2007
McGovern, Amy, and Fager, Jason. (2007) Creating Significant Learning Experiences in Introductory Artificial Intelligence. Proceedings of SIGCSE 2007, technical symposium on computer science education, pages 39-43. [pdf (223K)]
McGovern, Amy, and Rosendahl, Derek H., and Kruger, Adrianna, and Beaton, Meredith G., and Brown, Rodger A., and Droegemeier, Kelvin K. (2007) Understanding the formation of tornadoes through data mining. Preprints of the Fifth Conference on Artificial Intelligence and its Applications to Environmental Sciences at the American Meteorological Society annual conference. [pdf (1.9M)]
Dabney, William, and McGovern, Amy (2007) Utile Distinctions for Relational Reinforcement Learning. Proceedings of the International Joint Conference on Artificial Intelligence (IJCAI-07), pages 738-743. [pdf (490K)]
2006
McGovern, Amy, Kruger, Adrianna, Rosendahl, Derek, and Droegemeier, Kelvin. (2006) Open problem: Dynamic Relational Models for Improved Hazardous Weather Prediction. Presented at the ICML Workshop on Open Problems in Statistical Relational Learning. [pdf 204K]
Dabney, William and McGovern, Amy. (2006) The Thing That We Tried That Worked: Utile Distinctions for Relational Reinforcement Learning. Presented at the ICML Workshop on Open Problems in Statistical Relational Learning. [pdf 529K]
2005 and earlier
McGovern, Amy, Friedland, Lisa, Hay, Michael, Gallagher, Brian, Fast, Andrew, Neville, Jennifer, and Jensen, David (2003) Exploiting Relational Structure to Understand Publication Patterns in High-Energy Physics, Knowledge Discovery Laboratory, University of Massachusetts Amherst. (2003). SIGKDD Explorations, December 2003, Volume 5, Issue 2, pages 165-172. Winning entry to the open task for KDD Cup. [pdf (1.6MB)]
McGovern, Amy , and Jensen, David (2003) Identifying Predictive Structures in Relational Data Using Multiple Instance Learning. To appear in the Proceedings of the 20th International Conference on Machine Learning, pages TBD. [postscript (252K) | gzipped postscript (160K) | pdf (112K)]
McGovern, Amy (2002) Autonomous Discovery of Temporal Abstractions from Interaction with an Environment. University of Massachusetts Amherst. [postscript (1984K) | gzipped postscript (774K) | pdf (664K)]
McGovern, Amy , Moss, Eliot, and Andrew G. Barto (2002) Building a Basic Block Instruction Scheduler using Reinforcement Learning and Rollouts, Machine Learning, Special Issue on Reinforcement Learning. Volume 49, Numbers 2/3, Pages 141-160. [postscript (200K) | gzipped postscript (60K) | pdf (160K)]
McGovern, Amy , and Barto, Andrew G. (2001) Automatic Discovery of Subgoals in Reinforcement Learning using Diverse Density. Proceedings of the 18th International Conference on Machine Learning, pages 361-368. [postscript (252K) | gzipped postscript (160K) | pdf (112K)]
McGovern, Amy , and Barto, Andrew G. (2001) Accelerating Reinforcement Learning through the Discovery of Useful Subgoals. Proceedings of the 6th International Symposium on Artificial Intelligence, Robotics and Automation in Space: i-SAIRAS 2001, electronically published. [postscript (184K) | gzipped postscript (45K) | pdf (95K)]
McGovern, Amy , and Moss, Eliot (1998) Scheduling Straight-Line Code Using Reinforcement Learning and Rollouts, Proceedings of the 11th Neural Information Processing Systems Conference (NIPS '98), pages 903-909. [postscript (120K) | gzipped postscript (34K) | pdf (80K)]
Hofmann, Martin O., McGovern, Amy , Whitebread, Kenneth R. (1998) Mobile Agents Prevail in the Digital Battlefield. In the Proceedings of the 2nd International Conference on Autonomous Agents (Agents'98), pages 219-225. [postscript (696K) | gzipped postscript (200K) | pdf (80K)]
McGovern, Amy , Sutton, Richard S., Fagg, Andrew H. (1997) Roles of Macro-Actions in Accelerating Reinforcement Learning. 1997 Grace Hopper Celebration of Women in Computing, pages 13-18. [postscript (472K) | gzipped postscript(72K) | pdf(184K)]