Edited Volumes

Eric Eaton, Carla Gomes, and Brian Williams, editors. AI Magazine: Special Issue on Computational Sustainability, AAAI Press, 2014. [In Press]
Eric Eaton (chair). Lifelong Machine Learning: Proceedings of the 2013 AAAI Spring Symposium, AAAI Technical Report SS-13-05, AAAI Press, May 2013.
http://www.aaai.org/Press/Reports/Symposia/Spring/ss-13-05.php

Journals and Highly Selective Conferences

Paul Ruvolo and Eric Eaton. Online Multi-Task Learning via Sparse Dictionary Optimization. In Proceedings of the 28th AAAI Conference on Artificial Intelligence (AAAI-14), July 2014.
Haitham Bou Ammar, Eric Eaton, Paul Ruvolo, and Matthew E. Taylor. Online Multi-Task Learning for Policy Gradient Methods. In Proceedings of the 2014 International Conference on Machine Learning (ICML-14), June 2014.
Eric Eaton, Marie desJardins, and Sara Jacob. Multi-view constrained clustering with an incomplete mapping between views. Knowledge and Information Systems, 38(1):231–257, January 2014.
Published online November 2012, doi 10.1007/s10115-012-0577-7.
Eric Eaton, Carla Gomes, and Brian Williams. Computational Sustainability. AI Magazine, To Appear, 2014.
Paul Ruvolo and Eric Eaton. Active Task Selection for Lifelong Machine Learning. In Proceedings of the Twenty-Seventh AAAI Conference on Artificial Intelligence (AAAI-13), July 2013.
Paul Ruvolo and Eric Eaton. ELLA: An Efficient Lifelong Learning Algorithm. In Proceedings of the 2013 International Conference on Machine Learning (ICML-13), June 2013.
Eric Eaton and Rachael Mansbach. A spin-glass model for semi-supervised community detection. In Proceedings of the Twenty-Sixth AAAI Conference on Artificial Intelligence (AAAI-12), pp. 900–906, AAAI Press, July 22--26 2012.
Eric Eaton and Marie desJardins. Selective Transfer Between Learning Tasks Using Task-Based Boosting. In Proceedings of the Twenty-Fifth AAAI Conference on Artificial Intelligence (AAAI-11), pp. 337–342, AAAI Press, August 7--11 2011.
Eric Eaton, Marie desJardins, and Sara Jacob. Multi-View Clustering with Constraint Propagation for Learning with an Incomplete Mapping Between Views. In Proceedings of the Conference on Information and Knowledge Management (CIKM'10), pp. 389–398, ACM Press, October 26--30 2010.
Kiri Wagstaff, Marie desJardins, and Eric Eaton. Modeling and learning user preferences over sets. Journal of Experimental & Theoretical Artificial Intelligence, 22(3):237–268, September 2010.
Eric Eaton, Gary Holness, and Daniel McFarlane. Interactive Learning using Manifold Geometry. In Proceedings of the Twenty-Fourth AAAI Conference on Artificial Intelligence (AAAI-10), pp. 437–443, AAAI Press, July 11--15 2010.
Eric Eaton, Marie desJardins, and Terran Lane. Modeling Transfer Relationships Between Learning Tasks for Improved Inductive Transfer. In Proceedings of the 19th European Conference on Machine Learning, pp. 317–332, Springer-Verlag, Berlin, Heidelberg, 2008.
Acceptance rate: 20%
Marie desJardins, Eric Eaton, and Kiri Wagstaff. Learning user preferences for sets of objects. In Proceedings of the 23rd International Conference on Machine Learning, Pittsburgh, PA, June 25--29 2006.
See DDPref Software for associated code. Acceptance rate: 20%. Awarded recognition as a NASA Tech Brief in 2008

Refereed Workshops and Symposia

Paul Ruvolo and Eric Eaton. Online Multi-Task Learning based on K-SVD. In Proceedings of the ICML 2013 Workshop on Theoretically Grounded Transfer Learning, June 2013.
Superceded by the AAAI-14 paper Online Multi-Task Learning via Sparse Dictionary Optimization.
Paul Ruvolo and Eric Eaton. Scalable Lifelong Learning with Active Task Selection. In Proceedings of the AAAI 2013 Spring Symposium on Lifelong Machine Learning, March 25-27 2013.
Superceded by the AAAI-13 paper Active Task Selection for Lifelong Machine Learning.
Douglas Fisher, Bistra Dilkina, Eric Eaton, and Carla Gomes. Incorporating computational sustainability into AI education through a freely-available, collectively-composed supplementary lab text. In Proceedings of the Third AAAI Symposium on Educational Advances in Artificial Intelligence (EAAI-12), AAAI Press, July 23--24 2012.
Douglas Fisher, Bistra Dilkina, Eric Eaton, and Carla Gomes. Incorporating computational sustainability into AI education through a freely-available, collectively-composed supplementary lab text [Oral Presentation]. In the 3rd International Conference on Computational Sustainability (CompSust'12), July 5--6 2012.
Diane Oyen, Eric Eaton, and Terran Lane. Inferring tasks for improved network structure discovery. In Working Notes of the Snowbird Learning Workshop, April 3--6 2012.
Eric Eaton and Terran Lane. The Importance of Selective Knowledge Transfer for Lifelong Learning. In AAAI-11 Workshop on Lifelong Learning from Sensorimotor Data, AAAI Press, August 7 2011.
Eric Eaton and Marie desJardins. Set-Based Boosting for Instance-level Transfer. In Proceedings of the International Conference on Data Mining Workshop on Transfer Mining, pp. 422–428, IEEE Press, December 2009.
Superceded by the AAAI-11 paper Selective Transfer Between Learning Tasks Using Task-Based Boosting.
Eric Eaton, Gary Holness, and Daniel McFarlane. Interactive Learning using Manifold Geometry. In Proceedings of the AAAI Fall Symposium on Manifold Learning and Its Applications (AAAI Technical Report FS-09-04), pp. 10–17, AAAI Press, November 5--7 2009.
Superseded by the AAAI-10 conference paper Interactive Learning using Manifold Geometry.
Eric Eaton. Gridworld Search and Rescue: A Project Framework for a Course in Artificial Intelligence. In Proceedings of the AAAI-08 AI Education Colloquium, Chicago, IL, July 13 2008.
Eric Eaton, Marie desJardins, and Terran Lane. Using functions on a model graph for inductive transfer. In Proceedings of the Northeast Student Colloquium on Artificial Intelligence (NESCAI-08), Ithaca, NY, May 2--4 2008.
Superceded by the ECML-08 paper Modeling Transfer Relationships Between Learning Tasks for Improved Inductive Transfer.
Eric Eaton. Multi-Resolution Learning for Knowledge Transfer. In Proceedings of the 21st National Conference on Artificial Intelligence, AAAI Press, Boston, MA, July 16--20 2006. [Doctoral Consortium]
Eric Eaton and Marie desJardins. Knowledge Transfer with a Multiresolution Ensemble of Classifiers. In Proceedings of the ICML-06 Workshop on Structural Knowledge Transfer for Machine Learning, Pittsburgh, PA, June 29 2006.
Marie desJardins, Eric Eaton, and Kiri Wagstaff. A context-sensitive and user-centric approach to developing personal assistants. In Proceedings of the AAAI Spring Symposium on Persistent Assistants, pp. 98–100, Stanford, CA, March 21--23 2005.

Refereed Short Papers and Abstracts

Vishnu Purushothaman Sreenivasan, Haitham Bou Ammar, and Eric Eaton. Online Multi-Task Gradient Temporal-Difference Learning. In Proceedings of the 28th AAAI Conference on Artificial Intelligence (AAAI-14), July 2014. [Student Abstract]
Eric Eaton, Marie desJardins, and John Stevenson. Using multiresolution learning for transfer in image classification. In Proceedings of the 22nd National Conference on Artificial Intelligence, AAAI Press, Vancouver, British Columbia, Canada, 2007. [Student Abstract]

Dissertation and Thesis

Eric Eaton. Selective Knowledge Transfer for Machine Learning. Ph.D. Thesis, University of Maryland Baltimore County, 2009.
Eric Eaton. Clustering with Propagated Constraints. Master's Thesis, University of Maryland Baltimore County, 2005.

Technical Reports

Eric Eaton, Dan McFarlane, and Martin Hofmann. Analysis of Complex Data Using Heterogeneous Relational Models. Technical Report #DS-104-421-1610WP, Lockheed Martin Advanced Technology Laboratories, 6 pgs, March 2009.
Eric Eaton, Gary Holness, and Dan McFarlane. Situational Awareness through Interactive Learning. Technical Report #DS-104-421-1607WP, Lockheed Martin Advanced Technology Laboratories, 4 pgs, March 2009.
Meghann Lomas, Daniel McFarlane, Eric Eaton, Robert Szczerba, and Jerry Franke. Dynamic Ensemble Planning for Tactical Hierarchies. Technical Report #DS-104-421-1604WP, Lockheed Martin Advanced Technology Laboratories, 4 pgs, March 2009.
Eric Eaton, Katherine Guo, and Martin Hofmann. Predicting and Verifying Effects of Cyber Operations from Indirect Observations. Technical Report #DS-105-421-1598WP, Lockheed Martin Advanced Technology Laboratories, 5 pgs, January 2009.
Eric Eaton, Katherine Guo, and Martin Hofmann. Multimodal and Temporal Learning using Relational Networks. Technical Report #DS-105-421-1583RFI, Lockheed Martin Advanced Technology Laboratories, 7 pgs, November 2008.

Software

Eric Eaton. Gridworld Search and Rescue Software. Available online at: http://maple.cs.umbc.edu/ ericeaton/searchandrescue/, 2008.
Eric Eaton, Marie desJardins, and Kiri Wagstaff. DDPref Software: Learning preferences for sets of objects. Available online at: http://maple.cs.umbc.edu/ ericeaton/software/DDPref.zip, 2006.

Other

Eric Eaton and Padmavathia Mundur. A multi-tier architecture for video communication systems. Undergraduate Research and Creative Achievement Day, University of Maryland Baltimore County, Baltimore, MD, April 30 2003. [Poster]