Publications

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P. Sen and Getoor, L., Cost-Sensitive Learning with Conditional Markov Networks, Data Mining and Knowledge Discovery, Special Issue on Utility Based Data Mining, vol. 17, pp. 136–163, 2008.PDF icon draft.pdf (424.09 KB)
P. Sen and Getoor, L., Cost-Sensitive Learning with Conditional Markov Networks, in SIAM Data Mining Workshop on Link Analysis, Counterterrorism and Security, 2006.PDF icon sensiam_lacs06.pdf (137.37 KB)
P. Sen and Getoor, L., Cost-Sensitive Learning with Conditional Markov Networks, in International Conference on Machine Learning, 2006.PDF icon senicml06.pdf (118.33 KB)
V. Embar, Sisman, B., Wei, H., Dong, X. Luna, Faloutsos, C., and Getoor, L., Contrastive Entity Linkage: Mining Variational Attributes from Large Catalogs for Entity Linkage, in Automated Knowledge Base Construction (AKBC), 2020.PDF icon embar-akbc20.pdf (499.49 KB)
M. Broecheler and Getoor, L., Computing marginal distributions over continuous Markov networks for statistical relational learning, in Advances in Neural Information Processing Systems (NIPS), 2010.PDF icon broecheler-nips10.pdf (382.51 KB)
M. Polymeropoulos, Licamele, L., Volpi, S., Mack, K., Mitkus, S., Carstea, E., Getoor, L., and Lavedan, C., Common effect of antipsychotics on the biosynthesis and regulation of fatty acids and cholesterol supports a key role of lipid homeostasis in schizophrenia., Schizophrenia Research, 2009.
O. Udrea and Getoor, L., Combining statistical and logical inference for ontology alignment, in Workshop on Semantic Web for Collaborative Knowledge Acquisition at the International Joint Conference on Artificial Intelligence, 2007.
M. Bilgic, Namata, G. Mark, and Getoor, L., Combining Collective Classification and Link Prediction, in Workshop on Mining Graphs and Complex Structures at the IEEE International Conference on Data Mining (ICDM-2007), 2007.PDF icon mgcs07.pdf (105.13 KB)
D. Sridhar, Foulds, J., Huang, B., Walker, M., and Getoor, L., Collective classification of stance and disagreement in online debate forums, in Bay Area Machine Learning Symposium (BayLearn), 2014.
D. Sridhar, Getoor, L., and Walker, M., Collective Stance Classification of Posts in Online Debate Forums, in ACL Joint Workshop on Social Dynamics and Personal Attributes in Social Media, 2014.PDF icon sridhar-aclws14.pdf (190.8 KB)
B. London, Huang, B., Taskar, B., and Getoor, L., Collective Stability in Structured Prediction: Generalization from One Example, in ICML, 2013.PDF icon london-icml13.pdf (373.82 KB)
S. Fakhraei, Foulds, J., Shashanka, M., and Getoor, L., Collective Spammer Detection in Evolving Multi-Relational Social Networks, in KDD, 2015.PDF icon fakhraei-kdd2015.pdf (573.89 KB)
I. Bhattacharya and Getoor, L., Collective Relational Clustering, 1st ed., vol. 1. Chapman and Hall, 2008, pp. 221-244.PDF icon bhattacharya-book08.pdf (10.39 MB)
A. Kimmig, Memory, A., Miller, R., and Getoor, L., A Collective, Probabilistic Approach to Schema Mapping, in International Conference on Data Engineering (ICDE), 2017.PDF icon kimmig-icde17.pdf (463.69 KB)
S. Fakhraei, Huang, B., and Getoor, L., Collective Inference and Multi-Relational Learning for Drug–Target Interaction Prediction, in NIPS Workshop on MLCB, 2013.PDF icon fakhraei-mlcb13.pdf (243.86 KB)
G. Namata, Kok, S., and Getoor, L., Collective Graph Identification, in KDD, 2011.PDF icon namata-kdd11.pdf (185.7 KB)
G. Namata, London, B., and Getoor, L., Collective Graph Identification, TKDD, vol. 10, 2015.PDF icon namata-tkdd15.pdf (500.96 KB)
I. Bhattacharya and Getoor, L., Collective Entity Resolution in Relational Data, Data Engineering Bulletin, vol. 29, 2006.
P. Kouki, Pujara, J., Marcum, C., Koehly, L., and Getoor, L., Collective Entity Resolution in Multi-Relational Familial Networks, Knowledge and Information Systems (KAIS), vol. 61, no. 3, p. 1547-–1581, 2018.PDF icon kouki-kais18.pdf (1.17 MB)
P. Kouki, Pujara, J., Marcum, C., Koehly, L., and Getoor, L., Collective Entity Resolution in Familial Networks, in IEEE International Conference on Data Mining (ICDM), 2017.PDF icon kouki-icdm17.pdf (653.4 KB)
I. Bhattacharya and Getoor, L., Collective Entity Resolution In Relational Data, ACM Transactions on Knowledge Discovery from Data, vol. 1, pp. 1-36, 2007.PDF icon bhattacharya-tkdd.pdf (346.13 KB)
I. Bhattacharya, Collective Entity Resolution In Relational Data, University of Maryland, College Park, 2006.PDF icon thesis.pdf (761.21 KB)
B. London and Getoor, L., Collective Classification of Network Data, 1st ed., vol. 1. CRC Press, 2013, p. 399--416.PDF icon london-book13.pdf (394.37 KB)
P. Sen, Namata, G. Mark, Bilgic, M., Getoor, L., Gallagher, B., and Eliassi-Rad, T., Collective Classification in Network Data, AI Magazine, vol. 29, pp. 93–106, 2008.PDF icon sen-aimag08.pdf (497.82 KB)
G. Namata, Sen, P., Bilgic, M., and Getoor, L., Collective Classification for Text Classification, 1st ed., vol. 1. Taylor and Francis Group, 2009, p. 51--69.PDF icon namata-book09.pdf (4.35 MB)
P. Sen, Namata, G. Mark, Bilgic, M., and Getoor, L., Collective Classification, Encyclopedia of Machine Learning, 2010.
V. Embar, Pujara, J., and Getoor, L., Collective Alignment of Large-scale Ontologies, in AKBC Workshop on Federated Knowledge Bases (FKBs), 2019.PDF icon embar-fkbs19.pdf (57.36 KB)
B. London, Khamis, S., Bach, S., Huang, B., Getoor, L., and Davis, L., Collective Activity Detection using Hinge-loss Markov Random Fields, in CVPR Workshop on SPTLE, 2013.PDF icon london-sptle13.pdf (705.87 KB)
A. Lansky, Friedman, M., Getoor, L., Schmidler, S., and Jr., N. Short, The Collage/Khoros Link: Planning for Image Processing Tasks, in Proceedings of the AAAI Spring Symposium on Integrated Planning Applications, 1995.
E. Zheleva, Sharara, H., and Getoor, L., Co-evolution of Social and Affiliation Networks, in 15th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD), 2009.PDF icon fp659-zheleva.pdf (900 KB)
J. Pujara and Getoor, L., Coarse-to-Fine, Cost-Sensitive Classification of E-Mail, in NIPS Workshop on Coarse-to-Fine Processing, 2010.PDF icon pujara_nips10.pdf (258.86 KB)
J. Chang, Chen, R., Pujara, J., and Getoor, L., Clustering System Data using Aggregate Measures, in Machine Learning and Systems (MLSys), 2018.PDF icon chang-sysml18.pdf (299.32 KB)
R. Islamaj, Getoor, L., and W. Wilbur, J., Characterizing RNA secondary-structure features and their effects on splice-site prediction, in IEEE ICDM Workshop on Mining and Management of Biological Data, 2007.
J. Doppa, Yu, J., Tadepalli, P., and Getoor, L., Chance-Constrained Programs for Link Prediction, in NIPS Workshop on Analyzing Networks and Learning with Graphs, 2009.PDF icon doppa-nips09wkshp.pdf (161.38 KB)
B. Salami, Parikh, H., Kayali, M., Roy, S., Getoor, L., and Suciu, D., Causal Relational Learning, in International Conference on Management of Data (SIGMOD), 2020.PDF icon salami-sigmod20.pdf (1.02 MB)
S. Muthiah, Huang, B., Arredondo, J., Mares, D., Getoor, L., Katz, G., and Ramakrishnan, N., Capturing Planned Protests from Open Source Indicators, AI Mag, vol. 37, pp. 63–75, 2016.PDF icon muthiah-aimag16.pdf (1.23 MB)
L. Licamele, Bilgic, M., Getoor, L., and Roussopoulos, N., Capital and Benefit in Social Networks, in ACM SIGKDD Workshop on Link Analysis and Group Detection (LinkKDD), 2005.PDF icon licamele_linkkdd05.pdf (421.14 KB)
H. Kang, Getoor, L., and Singh, L., C-GROUP: A Visual Analytic Tool for Pairwise Analysis of Dynamic Group Membership, in Visual Analytics Science and Technology (VAST), 2007.PDF icon vast07-kang.pdf (663.26 KB)
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J. Pujara and Getoor, L., Building Dynamic Knowledge Graphs, in NIPS Workshop on Automated Knowledge Base Construction, 2014.PDF icon pujara_akbc14.pdf (143.26 KB)
J. Pujara, London, B., and Getoor, L., Budgeted Online Collective Inference, in UAI, 2015.PDF icon pujara-uai15.pdf (302.63 KB)
P. Sen, Deshpande, A., and Getoor, L., Bisimulation-based Approximate Lifted Inference, in Uncertainty in Artificial Intelligence, 2009.PDF icon uai09.pdf (240.89 KB)
N. Ramakrishnan, Butler, P., Self, N., Khandpur, R., Saraf, P., Wang, W., Cadena, J., Vullikanti, A., Korkmaz, G., Kuhlman, C., Marathe, A., Zhao, L., Ting, H., Huang, B., Srinivasan, A., Trinh, K., Getoor, L., Katz, G., Doyle, A., Ackermann, C., Zavorin, I., Ford, J., Summers, K., Fayed, Y., Arredondo, J., Gupta, D., and Mares, D., ‘Beating the news’ with EMBERS: Forecasting Civil Unrest using Open Source Indicators, in ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2014.PDF icon ramakrishnan-kdd14.pdf (1.15 MB)
M. desJardins, Rathod, P., and Getoor, L., Bayesian Network Learning with Abstraction Hierarchies and Context-Specific Independence, in 16th European Conference on Machine Learning (ECML), 2005.
S. Srinivasan, Farnadi, G., and Getoor, L., BOWL: Bayesian Optimization for Weight Learning in Probabilistic Soft Logic, in AAAI Conference on Artificial Intelligence (AAAI), 2020.PDF icon srinivasan-aaai20a.pdf (478.65 KB)

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