Publications

MacArthur CA, Shneiderman B. 1986. Learning disabled students' difficulties in learning to use a word processor: implications for design. ACM SIGCHI Bulletin. 17(3):41-46.

Aloimonos Y, Shulman D. 1989. Learning early-vision computations. JOSA A. 6(6):908-919.

Ramanathan N, Chellappa R. 2009. Learning Facial Aging Models: A Face Recognition Perspective. Biometrics: theory, methods, and applications. 9:271-271.

Selby RW, Porter A. 1988. Learning from examples: generation and evaluation of decision trees for software resource analysis. IEEE Transactions on Software Engineering. 14(12):1743-1757.

Lin Z, Davis LS. 2008. Learning pairwise dissimilarity profiles for appearance recognition in visual surveillance. Advances in Visual Computing. :23-34.

Ilghami O, Nau DS, Muñoz-Avila H, Aha DW. 2005. Learning preconditions for planning from plan traces and HTN structure. Computational Intelligence. 21(4):388-413.

Getoor L, Friedman N, Koller D, Taskar B. 2001. Learning probabilistic models of relational structure. MACHINE LEARNING-INTERNATIONAL WORKSHOP. :170-177.

Friedman N, Getoor L, Koller D, Pfeffer A. 1999. Learning probabilistic relational models. International Joint Conference on Artificial Intelligence. 16:1300-1309.

Getoor L. 2000. Learning probabilistic relational models. Abstraction, Reformulation, and Approximation. :322-323.

Gruser JR, Raschid L, Zadorozhny V, Zhan T. 2000. Learning response time for websources using query feedback and application in query optimization. The VLDB Journal—The International Journal on Very Large Data Bases. 9(1):18-37.

Aloimonos Y, Shulman D. 1987. Learning shape computations. Proc. DARPA Image.

Getoor L. 2003. Learning Structure From Statistical Models. IEEE Data Engineering Bulletin. 26(3):11-18.

desJardins M, Rathod P, Getoor L. 2008. LEARNING STRUCTURED BAYESIAN NETWORKS: COMBINING ABSTRACTION HIERARCHIES AND TREE‐STRUCTURED CONDITIONAL PROBABILITY TABLES. Computational Intelligence. 24(1):1-22.

Getoor L, Friedman N, Koller D. 2002. Learning structured statistical models from relational data. Linköping Electronic Articles in Computer and Information Science. 7:13-13.

Sato T, Kameya Y, De Raedt L, Dietterich T, Getoor L, Muggleton SH. 2006. Learning through failure. Probabilistic, Logical and Relational Learning-Towards a Synthesis. (05051)

Ahmed Syed N, Feamster N, Gray A. 2008. Learning To Predict Bad Behavior. NIPS 2007 Workshop on Machine Learning in Adversarial Environments for Computer Security.

Mihalkova L, Moustafa W, Getoor L. 2011. Learning to predict web collaborations. Workshop on User Modeling for Web Applications (UMWA-11).

Smith M, desJardins M. 2009. Learning to trust in the competence and commitment of agents. Autonomous Agents and Multi-Agent Systems. 18(1):36-82.

Jain A, Gupta A, Davis LS. 2010. Learning what and how of contextual models for scene labeling. Computer Vision–ECCV 2010. :199-212.

Erickson J, Har-Peled S, Mount D. 2006. On the Least Median Square Problem. Discrete & Computational Geometry. 36(4):593-607.

Elman H, Howle VE, Shadid J, Silvester D, Tuminaro R. 2007. Least squares preconditioners for stabilized discretizations of the Navier-Stokes equations. SIAM J. Sci. Comput. 30(1):290-311.

Murray GC, Dorr BJ, Jimmy Lin, Hajič J, Pecina P. 2006. Leveraging recurrent phrase structure in large-scale ontology translation. Proceedings of the 11th Annual Conference of the European Association for Machine Translation.

Voss CR, Dorr BJ, Sencan MU. 1995. Lexical allocation in interlingua-based machine translation of spatial expressions. Working Notes for IJCAI-95 Workshop on the Representation and Processing of Spatial Expressions, Montreal, Canada.

Nguyen V-A, Boyd-Graber J, Resnik P. 2013. Lexical and Hierarchical Topic Regression. :1106-1114.

Rose A, Ellis J, Plaisant C, Greene S. 1998. Life cycle of user interface techniques: The DJJ information system design Process. Technical Reports of the Computer Science Department.

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Publications