Publications

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L
London, B., Rekatsinas, T., Huang, B. & Getoor, L. Multi-relational Weighted Tensor Decomposition. NIPS Workshop on Spectral Learning (2012).PDF icon london-nips12ws-mrwtd.pdf (326.3 KB)
London, B. On the Stability of Structured Prediction. (2015).PDF icon blondon-thesis.pdf (1.16 MB)
London, B., Huang, B. & Getoor, L. Stability and Generalization in Structured Prediction. (2015).PDF icon london-stability15.pdf (532.16 KB)
London, B., Huang, B. & Getoor, L. The Benefits of Learning with Strongly Convex Approximate Inference. International Conference on Machine Learning (ICML) (2015).PDF icon london-icml15.pdf (788.06 KB)
London, B., Huang, B. & Getoor, L. Stability and Generalization in Structured Prediction. Journal of Machine Learning Research 17, (2016).PDF icon london-jlmr17.pdf (532.8 KB)
London, B., Huang, B. & Getoor, L. On the Strong Convexity of Variational Inference. NIPS Workshop on Advances in Variational Inference (2014).PDF icon london-nips14ws.pdf (253.72 KB)
Licamele, L. & Getoor, L. A method for the detection of meaningful and reproducible group signatures from gene expression profiles. Journal of Bioinformatics and Computational Biology (2011).
Licamele, L. & Getoor, L. Indirect two-sided relative ranking: a robust similarity measure for gene expression data. BMC Bioinformatics (2010).
Licamele, L. & Getoor, L. Predicting Protein-Protein Interactions Using Relational Features. ICML Workshop on Statistical Network Analysis (2006).
Licamele, L. & Getoor, L. Social Capital in Friendship-Event Networks. IEEE International Conference on Data Mining (ICDM) (2006).
Licamele, L., Bilgic, M., Getoor, L. & Roussopoulos, N. Capital and Benefit in Social Networks. ACM SIGKDD Workshop on Link Analysis and Group Detection (LinkKDD) (2005).PDF icon licamele_linkkdd05.pdf (421.14 KB)
Lerman, K., Getoor, L., Minton, S. & Knoblock, C. Using the Structure of Web Sites for Automatic Segmentation of Tables. In Proceedings of ACM-SIGMOD 2004 International Conference on Management of Data (2004).PDF icon lerman-sigmod04.pdf (307.43 KB)
Lansky, A. & Getoor, L. Scope and Abstraction: Two Criteria for Localized Planning. Proceedings of the International Joint Conference on Arti cial Intelligence (1995).
Lansky, A., Friedman, M., Getoor, L., Schmidler, S. & Jr., N. Short. The Collage/Khoros Link: Planning for Image Processing Tasks. Proceedings of the AAAI Spring Symposium on Integrated Planning Applications (1995).
Lansky, A. & Getoor, L. Practical Planning in COLLAGE. Proceedings of the AAAI Fall Symposium on Planning and Learning: On to Real Applications (1994).
Lansky, A. & Getoor, L. Scope and Abstraction: Two Criteria for Localized Planning. Proceedings of the Workshop on Theory Reformulation and Abstraction (1994).
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Kumar, S. et al. Unsupervised Models for Predicting Strategic Relations between Organizations. IEEE ACM International Conference on Advances in Social Networks Analysis and Mining (IEEE, 2016).PDF icon kumar_asonam16.pdf (212.61 KB)
Kouki, P., Pujara, J., Marcum, C., Koehly, L. & Getoor, L. Collective Entity Resolution in Familial Networks. IEEE International Conference on Data Mining (ICDM) (2017). at <https://github.com/pkouki/icdm2017>PDF icon kouki-icdm17.pdf (653.4 KB)
Kouki, P., Schaffer, J., Pujara, J., ODonovan, J. & Getoor, L. User Preferences for Hybrid Explanations. 11th ACM Conference on Recommender Systems (RecSys) (2017).PDF icon kouki-recsys17.pdf (2.64 MB)
Kouki, P., Fakhraei, S., Foulds, J., Eirinaki, M. & Getoor, L. HyPER: A Flexible and Extensible Probabilistic Framework for Hybrid Recommender Systems. 9th ACM Conference on Recommender Systems (RecSys) (ACM, 2015).PDF icon kouki-recsys15.pdf (1.03 MB)
Kouki, P., Marcum, C., Koehly, L. & Getoor, L. Entity Resolution in Familial Networks. 12th International Workshop on Mining and Learning with Graphs (2016).PDF icon kouki-mlg16.pdf (633.08 KB)
Kouki, P., Pujra, J., Marcum, C., Koehly, L. & Getoor, L. Collective Entity Resolution in Multi-Relational Familial Networks. Knowledge and Information Systems (KAIS) (2018).PDF icon kouki-kais18.pdf (1.17 MB)
Kouki, P. Resolution, Recommendation, and Explanation in Richly Structured Social Networks. Technology and Information Management Ph.D. Thesis, (2018).PDF icon kouki-dissertation.pdf (6.94 MB)
Kouki, P., Schaffer, J., Pujara, J., ODonovan, J. & Getoor, L. Personalized Explanations for Hybrid Recommender Systems. Intelligent User Interfaces (2019).PDF icon kouki-iui19.pdf (3.34 MB)
Koller, D., Friedman, N., Getoor, L. & Taskar, B. An Introduction to Statistical Relational Learning (Getoor, L. & Taskar, B.) (MIT Press, 2007).PDF icon srlbook-ch2.pdf (513.11 KB)
Kimmig, A., Mihalkova, L. & Getoor, L. Lifted graphical models: a survey. Machine Learning 1-45 (2014).
Kimmig, A., Bach, S. H., Broecheler, M., Huang, B. & Getoor, L. A Short Introduction to Probabilistic Soft Logic. NIPS Workshop on Probabilistic Programming: Foundations and Applications (2012).PDF icon psl_pp12.pdf (164.6 KB)
Kimmig, A., Memory, A., Miller, R. & Getoor, L. A Collective, Probabilistic Approach to Schema Mapping. International Conference on Data Engineering (ICDE) (2017). at <https://github.com/alexmemory/kimmig-icde17/wiki>PDF icon kimmig-icde17.pdf (463.69 KB)
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)
Kimmig, A., Memory, A., Miller, R. J. & Getoor, L. A Collective, Probabilistic Approach to Schema Mapping Using Diverse Noisy Evidence. IEEE Transactions on Knowledge and Data Engineering 31, 1426-1439 (2019).PDF icon kimming-tkde19.pdf (713.64 KB)
Kim, S., Kini, N., Pujara, J., Koh, E. & Getoor, L. Probabilistic Visitor Stitching on Cross-Device Web Logs. International Conference on World Wide Web (WWW) 1581–1589 (2017).PDF icon p1581-kimwww17.pdf (1.23 MB)
Kang, J., Lerman, K. & Getoor, L. LA-LDA: A Limited Attention Topic Model for Social Recommendation. The 2013 International Conference on Social Computing, Behavioral-Cultural Modeling, & Prediction (SBP 2013) (2013).PDF icon kang-sbp13.pdf (622.52 KB)
Kang, H., Getoor, L., Shneiderman, B., Bilgic, M. & Licamele, L. Interactive Entity Resolution in Relational Data: A Visual Analytic Tool and Its Evaluation. IEEE Transactions on Visualization and Computer Graphics 14, 999–1014 (2008).PDF icon kang-tvcg08.pdf (3.63 MB)
Kang, H., Getoor, L. & Singh, L. C-GROUP: A Visual Analytic Tool for Pairwise Analysis of Dynamic Group Membership. Visual Analytics Science and Technology (VAST) (2007).PDF icon vast07-kang.pdf (663.26 KB)
Kang, H., Sehgal, V. & Getoor, L. GeoDDupe: A Novel Interface for Interactive Entity Resolution in Geospatial Data. International Conference on Information Visualization (IEEE Computer Society, 2007).PDF icon kangiv07.pdf (1.34 MB)
Kang, H., Getoor, L. & Singh, L. Visual Analysis of Dynamic Group Membership in Temporal Social Networks. SIGKDD Explorations, Special Issue on Visual Analytics 9, 13-21 (2007).PDF icon 2_kang-CGROUP_1207.pdf (1.48 MB)
H
Hwang, H., Lauw, H., Getoor, L. & Ntoulas, A. Organizing User Search Histories. IEEE Transactions on Knowledge and Data Engineering (2010).
Hung, E., Getoor, L. & Subrahmanian, V. S. Probabilistic Interval XML. ACM Transactions on Computational Logic (TOCL) (2007).
Hung, E., Getoor, L. & Subrahmanian, V. S. Probabilistic Interval XML. Proceedings of the International Conference on Database Theory (2003).
Hung, E., Getoor, L. & Subrahmanian, V. S. PXML: A Probabilistic Semistructured Data Model and Algebra. Proceedings of the IEEE International Conference on Data Engineering (2003).
Huang, B., Kimmig, A., Getoor, L. & Golbeck, J. A Flexible Framework for Probabilistic Models of Social Trust. The 2013 International Conference on Social Computing, Behavioral-Cultural Modeling, & Prediction (SBP 2013) (2013).PDF icon huang-sbp13.pdf (247.2 KB)
Huang, B., London, B., Taskar, B. & Getoor, L. Empirical Analysis of Collective Stability. ICML Workshop on Structured Learning (SLG) (2013).PDF icon huang-slg13.pdf (237.81 KB)
Huang, B., Kimmig, A., Getoor, L. & Golbeck, J. Probabilistic Soft Logic for Trust Analysis in Social Networks. International Workshop on Statistical Relational Artificial Intelligence (StaRAI 2012) (2012).PDF icon huang-starai12.pdf (241.96 KB)
Huang, B., Bach, S. H., Norris, E., Pujara, J. & Getoor, L. Social Group Modeling with Probabilistic Soft Logic. NIPS 2012 Workshop - Social Network and Social Media Analysis: Methods, Models, and Applications (2012).

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