Publications

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L
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).
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)
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)
London, B., Huang, B., Taskar, B. & Getoor, L. PAC-Bayesian Collective Stability. Proceedings of the 17th International Conference on Artificial Intelligence and Statistics (2014).PDF icon london-aistats14.pdf (490.14 KB)
London, B. et al. Collective Activity Detection using Hinge-loss Markov Random Fields. CVPR Workshop on Structured Prediction: Tractability, Learning and Inference (2013).PDF icon london-cvpr13.pdf (705.87 KB)
London, B. & Getoor, L. Data Classification: Algorithms and Applications (Aggarwal, C.) (CRC Press, 2013).PDF icon cc-chapter.pdf (394.37 KB)
London, B., Huang, B., Taskar, B. & Getoor, L. Collective Stability in Structured Prediction: Generalization from One Example. Proceedings of the 30th International Conference on Machine Learning (ICML-13) (2013).PDF icon london-icml13-long.pdf (373.82 KB)
London, B., Huang, B. & Getoor, L. Graph-based Generalization Bounds for Learning Binary Relations. (2013).PDF icon br_risk_bounds.pdf (304.54 KB)
London, B., Rekatsinas, T., Huang, B. & Getoor, L. Multi-relational Learning Using Weighted Tensor Decomposition with Modular Loss. (2013).PDF icon mrwtd.pdf (460.45 KB)
London, B., Huang, B., Taskar, B. & Getoor, L. PAC-Bayes Generalization Bounds for Randomized Structured Prediction. NIP Workshop on Perturbation, Optimization and Statistics (2013).PDF icon london-nips13ws.pdf (205.57 KB)
London, B., Huang, B. & Getoor, L. Improved Generalization Bounds for Large-scale Structured Prediction. NIPS Workshop on Algorithmic and Statistical Approaches for Large Social Networks (2012).PDF icon london-nips12ws.pdf (213.95 KB)
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)
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)
M
Memory, A., Kimmig, A., Bach, S. H., Raschid, L. & Getoor, L. Graph Summarization in Annotated Data Using Probabilistic Soft Logic. Proceedings of the International Workshop on Uncertainty Reasoning for the Semantic Web (URSW) (2012).PDF icon mrc_iswc12_ws.pdf (411.71 KB)
Miao, H., Liu, X., Huang, B. & Getoor, L. A Hypergraph-Partitioned Vertex Programming Approach for Large-scale Consensus Optimization. 2013 IEEE International Conference on Big Data (2013).PDF icon miao-bd13.pdf (307.51 KB)
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)
Mihalkova, L. & Getoor, L. Lifted Graphical Models: A Survey. (2011).PDF icon 1107.4966v2.pdf (446.54 KB)
Minton, S. et al. Improving Classifier Performance by Autonomously Collecting Background Knowledge from the Web. Tenth International Conference on Machine Learning and Applications (2011).PDF icon minton-icmla2011.pdf (733.09 KB)
Moustafa, W. Eldin, Kimmig, A., Deshpande, A. & Getoor, L. Subgraph Pattern Matching over Uncertain Graphs with Identity Linkage Uncertainty. International Conference on Data Engineering (ICDE) (2014).PDF icon ICDE14_conf_full_374.pdf (1.57 MB)
Moustafa, W. Eldin, Miao, H., Deshpande, A. & Getoor, L. GrDB: A System for Declarative and Interactive Analysis of Noisy Information Networks. ACM SIGMOD Conference (2013).PDF icon sigmod13.pdf (1.1 MB)
Moustafa, W. Eldin, Deshpande, A. & Getoor, L. Ego-centric Graph Pattern Census. International Conference on Data Engineering (ICDE) (2012).PDF icon moustafaicde.pdf (2.27 MB)
Moustafa, W. Eldin, Namata, G. Mark, Deshpande, A. & Getoor, L. Declarative Analysis of Noisy Information Networks. ICDE Workshop on Graph Data Management: Techniques and Applications (2011).PDF icon moustafa-gdm11.pdf (1.55 MB)
Muthiah, S. et al. Capturing Planned Protests from Open Source Indicators. AI Magazine 37, 63–75 (2016).PDF icon muthiah-aimag16.pdf (1.23 MB)
N
Namata, G. Mark. Identifying Graphs from Noisy Observational Data. (2012).PDF icon namata-phdthesis.pdf (1.51 MB)
Namata, G. Mark, London, B., Getoor, L. & Huang, B. Query-driven Active Surveying for Collective Classification. Workshop on Mining and Learning with Graphs (2012).PDF icon namata-mlg12.pdf (257.49 KB)
Namata, G. Mark, Kok, S. & Getoor, L. Collective Graph Identification. ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (2011).PDF icon namata-kdd11.pdf (185.7 KB)
Namata, G. Mark, Sharara, H. & Getoor, L. Link Mining: Models, Algorithms, and Applications (Yu, J. Han Philip & Faloutsos, C.) (Springer, 2010).
Namata, G. Mark & Getoor, L. Link Prediction. Encyclopedia of Machine Learning (2010).
Namata, G. Mark & Getoor, L. A Pipeline Approach to Graph Identification. Seventh International Workshop on Mining and Learning with Graphs (2009).PDF icon namatag-mlg09.pdf (93.77 KB)
Namata, G. Mark, Sen, P., Bilgic, M. & Getoor, L. Text Mining: Classification, Clustering, and Applications (Sahami, M. & Srivastava, A.) (Taylor and Francis Group, 2009).
Namata, G. Mark & Getoor, L. Identifying Graphs From Noisy and Incomplete Data. 1st ACM SIGKDD Workshop on Knowledge Discovery from Uncertain Data (2009).PDF icon namatag-kddu09.pdf (241.7 KB)
Namata, G. Mark, Staats, B., Getoor, L. & Shneiderman, B. A Dual-View Approach to Interactive Network Visualization. ACM Conference on Information and Knowledge Management (2007).PDF icon cikm0671-namata.pdf (376.54 KB)
Namata, G. Mark, Getoor, L. & Diehl, C. Inferring Organizational Titles in Online Communications. ICML Workshop on Statistical Network Analysis (2006).PDF icon icml2006_ExtAbst.pdf (72.39 KB)
Namata, G. Mark, London, B. & Getoor, L. Collective Graph Identification. ACM Transactions on Knowledge Discovery from Data 10, 25:1–25:36 (2015).PDF icon namata-tkdd.pdf (500.96 KB)
P
Papadimitriou, P., Tsaparas, P., Fuxman, A. & Getoor, L. TACI: Taxonomy-Aware Catalog Integration. IEEE Transactions on Knowledge and Data Engineering (2012).
Piatetsky-Shapiro, G. et al. Is there a grand challenge or X-prize for data mining?. 12th International Conference on Knowledge Discovery and Data Mining (2006).

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