Publications

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Doppa, J., Yu, J., Tadepalli, P. & Getoor, L. Learning Algorithms for Link Prediction based on Chance Constraints. European Conference on Machine Learning (ECML) (2010).PDF icon doppa-ecml10.pdf (203 KB)
Ramesh, A., Goldwasser, D., Huang, B., III, H. Daume & Getoor, L. Learning Latent Engagement Patterns of Students in Online Courses. Proceedings of the Twenty-Eighth AAAI Conference on Artificial Intelligence (AAAI Press, 2014).PDF icon ramesh-aaai14.pdf (505.47 KB)
Bach, S. H., Huang, B. & Getoor, L. Learning Latent Groups with Hinge-loss Markov Random Fields. ICML Workshop on Inferning: Interactions between Inference and Learning (2013).PDF icon bach-inferning13.pdf (348.79 KB)
Getoor, L., Friedman, N., Koller, D. & Taskar, B. Learning Probabilistic Models of Link Structure. Journal of Machine Learning Research 3, 679- -707 (2002).PDF icon jmlr02.pdf (502.22 KB)
Getoor, L., Friedman, N., Koller, D. & Taskar, B. Learning Probabilistic Models of Relational Structure. Proceedings of International Conference on Machine Learning (ICML) (2001).PDF icon icml01.pdf (157.91 KB)
Getoor, L., Friedman, N., Koller, D. & Pfeffer, A. Relational Data Mining (Dzeroski, S. & Lavrac, N.) (Springer-Verlag, 2001).
Friedman, N., Getoor, L., Koller, D. & Pfeffer, A. Learning Probabilistic Relational Models. International Joint Conference on Arti cial Intelligence (1999).PDF icon icjai99.pdf (156.94 KB)
Getoor, L., Friedman, N., Koller, D. & Pfeffer, A. Learning Probabilistic Relational Models. Relational Data Mining (Springer-Verlag, 2001).PDF icon lprm-ch.pdf (376 KB)
Getoor, L., Koller, D., Taskar, B. & Friedman, N. Learning Probabilistic Relational Models with Structural Uncertainty. Proceedings of the AAAI Workshop on Learning Statistical Models from Relational Data (2000).
Getoor, L. Learning Statistical Models from Relational Data. (2001).PDF icon getoor-thesis.pdf (3.39 MB)
Getoor, L., Friedman, N. & Koller, D. Learning Structured Statistical Models from Relational Data. Electronic Transactions on Artificial Intelligence 6, (2002).
Mihalkova, L., Moustafa, W. Eldin & Getoor, L. Learning to Predict Web Collaborations. WSDM Workshop on User Modeling for Web Applications (2011).PDF icon mihalkova-wikiCollabs.pdf (353.9 KB)
Udrea, O., Getoor, L. & Miller, R. Leveraging Data and Structure in Ontology Integration. Proceedings of ACM-SIGMOD 2007 International Conference on Management 449–460 (2007).PDF icon p449.pdf (509.48 KB)
Smith, M., Barash, V., Getoor, L. & Lauw, H. Leveraging Social Context for Searching Social Media. CIKM Workshop on Search in Social Media (2008).
Mihalkova, L. & Getoor, L. Lifted Graphical Models: A Survey. (2011).PDF icon 1107.4966v2.pdf (446.54 KB)
Srinivasan, S., Babaki, B., Farnadi, G. & Getoor, L. Lifted Hinge-Loss Markov Random Fields. 33rd AAAI Conference on Artificial Intelligence (2019).PDF icon srinivasan-aaai19.pdf (417.5 KB)
Kimmig, A., Mihalkova, L. & Getoor, L. Lifted graphical models: a survey. Machine Learning 1-45 (2014).
Kimmig, A., Mihalkova, L. & Getoor, L. Lifted graphical models: a survey. Machine Learning Journal 99, 1–45 (2015).PDF icon kimmig-mlj15.pdf (785.58 KB)
Getoor, L. Link Mining: A New Data Mining Challenge. SIGKDD Explorations, volume 5, 85- -89 (2003).
Getoor, L. & Diehl, C. Link Mining: A Survey. SigKDD Explorations Special Issue on Link Mining 7, (2005).
Namata, G. Mark & Getoor, L. Link Prediction. Encyclopedia of Machine Learning (2010).
Bilgic, M. & Getoor, L. Link-based Active Learning. NIPS Workshop on Analyzing Networks and Learning with Graphs (2009).PDF icon mbilgic-nips09wkshp.pdf (116.35 KB)
Sen, P. & Getoor, L. Link-based Classification. (2007).PDF icon senum-tr07.pdf (511.11 KB)
Getoor, L. Advanced Methods for Knowledge Discovery from Complex Data (Maulik, U., Holder, L. & Cook, D.) (Springer-Verlag, 2005).
Lu, Q. & Getoor, L. Link-based Classification. Proceedings of the International Conference on Machine Learning (ICML) (2003).PDF icon lu-icml03.pdf (195.81 KB)
Lu, Q. & Getoor, L. Link-based Classification Using Labeled and Unlabeled Data. ICML Workshop on "The Continuum from Labeled to Unlabeled Data in Machine Learning and Data Mining (2003).PDF icon icml03-ws.pdf (274.65 KB)
Lu, Q. & Getoor, L. Link-based Text Classification. IJCAI Workshop on "Text Mining and Link Analysis" (2003).PDF icon ijcai03-ws.pdf (97.25 KB)
Rekatsinas, T., Deshpande, A. & Getoor, L. Local Structure and Determinism in Probabilistic Databases. ACM SIGMOD Conference (2012).PDF icon sigmod_AAC2012.pdf (490.28 KB)
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Bhattacharya, I. & Getoor, L. Online Collective Entity Resolution. The 22nd National Conference on Artificial Intelligence (NECTAR Track) (AAAI Press, 2007).PDF icon nectar07.pdf (395.24 KB)
Pujara, J., London, B., Getoor, L. & Cohen, W. Online Inference for Knowledge Graph Construction. Workshop on Statistical Relational AI (2015).PDF icon pujara-starai15.pdf (340.95 KB)
Getoor, L. & Fromherz, M. Online Scheduling for Reprographic Machines. Working notes AAAI Workshop on Online Search (1997).
Pujara, J., Miao, H., Getoor, L. & Cohen, W. Ontology-Aware Partitioning for Knowledge Graph Identification. CIKM Workshop on Automatic Knowledge Base Construction (2013).PDF icon pujara_akbc13.pdf (370.62 KB)
Somasundaran, S., Namata, G. Mark, Getoor, L. & Wiebe, J. Opinion Graphs for Polarity and Discourse Classification. TextGraphs-4: Graph-based Methods for Natural Language Processing (2009).PDF icon somasundaran-textgraphs09.pdf (289.75 KB)
Hwang, H., Lauw, H., Getoor, L. & Ntoulas, A. Organizing User Search Histories. IEEE Transactions on Knowledge and Data Engineering (2010).

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