Publications

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P
L. Getoor and Grant, J., PRL: A Logical Approach to Probabilistic Relational Models, Machine Learning Journal, vol. 62, 2006.PDF icon getoor-mlj06.pdf (685.04 KB)
E. Hung, Getoor, L., and Subrahmanian, V. S., PXML: A Probabilistic Semistructured Data Model and Algebra, in Proceedings of the IEEE International Conference on Data Engineering, 2003.
S. H. Bach, Huang, B., Boyd-Graber, J., and Getoor, L., Paired-Dual Learning for Fast Training of Latent Variable Hinge-Loss MRFs, in International Conference on Machine Learning (ICML), 2015.PDF icon bach-icml15.pdf (356.46 KB)
T. Elsayed, Oard, D., Namata, G. Mark, and Getoor, L., Personal Name Resolution in Email: A Heuristic Approach. University of Maryland, College Park, 2008.PDF icon LAMP_150.pdf (397.61 KB)
P. Kouki, Schaffer, J., Pujara, J., Odonovan, J., and Getoor, L., Personalized Explanations for Hybrid Recommender Systems, in Intelligent User Interfaces (IUI), 2019.PDF icon kouki-iui19.pdf (3.34 MB)
G. Mark Namata and Getoor, L., A Pipeline Approach to Graph Identification, in Seventh International Workshop on Mining and Learning with Graphs, 2009.PDF icon namatag-mlg09.pdf (93.77 KB)
P. Sen, Deshpande, A., and Getoor, L., PrDB: Managing and Exploiting Rich Correlations in Probabilistic Databases, VLDB Journal, special issue on uncertain and probabilistic databases, 2009.PDF icon sen-vldbj09.pdf (1.12 MB)
A. Lansky and Getoor, L., Practical Planning in COLLAGE, in Proceedings of the AAAI Fall Symposium on Planning and Learning: On to Real Applications, 1994.
S. Tomkins, Ramesh, A., and Getoor, L., Predicting Post-Test Performance from Online Student Behavior: A High School MOOC Case Study, in EDM, 2016.PDF icon tomkins-edm16.pdf (619.77 KB)
L. Licamele and Getoor, L., Predicting Protein-Protein Interactions Using Relational Features, in ICML Workshop on Statistical Network Analysis, 2006.
E. Zheleva and Getoor, L., Preserving the Privacy of Sensitive Relationships in Graph Data, in Proceedings of the First SIGKDD International Workshop on Privacy, Security, and Trust in KDD (PinKDD 2007), 2008, vol. 4890, pp. 153-171.
E. Zheleva and Getoor, L., Preserving the Privacy of Sensitive Relationships in Graph Data, in First ACM SIGKDD Workshop on Privacy, Security, and Trust in KDD (PinKDD 2007), 2007.PDF icon zheleva-pinkdd07.pdf (373.86 KB)
E. Zheleva, Terzi, E., and Getoor, L., Privacy in Social Networks, vol. 4. Morgan & Claypool Publishers, 2012.
E. Zheleva and Getoor, L., Privacy in Social Networks: A Survey, vol. 1. Springer, 2011, pp. 247–276.PDF icon zheleva-book11.pdf (791.3 KB)
A. Plangprasopchok, Lerman, K., and Getoor, L., A Probabilistic Approach for Learning Folksonomies from Structured Data, in Fourth ACM International Conference on Web Search and Data Mining (WSDM), 2011.
D. Sridhar and Getoor, L., Probabilistic Inference for Causal Structure Discovery, in UAI Workshop on Causation, 2016.PDF icon sridhar-causation16.pdf (118.31 KB)
E. Hung, Getoor, L., and Subrahmanian, V. S., Probabilistic Interval XML, ACM Transactions on Computational Logic (TOCL), 2007.
E. Hung, Getoor, L., and Subrahmanian, V. S., Probabilistic Interval XML, in Proceedings of the International Conference on Database Theory, 2003.
L. Getoor, Segal, E., Taskar, B., and Koller, D., Probabilistic Models of Text and Link Structure for Hypertext Classification, in IJCAI Workshop on Text Learning: Beyond Supervision, 2001.PDF icon ijcai01-ws.pdf (127.03 KB)
L. Getoor, Friedman, N., Koller, D., Pfeffer, A., and Taskar, B., Probabilistic Relational Models, 1st ed., vol. 1. MIT Press, 2007, p. 129--174.PDF icon getoor-book07.pdf (648.15 KB)
L. Getoor, Friedman, N., Koller, D., Pfeffer, A., and Taskar, B., Probabilistic Relational Models, 1st ed., vol. 1. MIT Press, 2007, p. 129--174.PDF icon getoor-book07.pdf (648.15 KB)
M. Broecheler, Mihalkova, L., and Getoor, L., Probabilistic Similarity Logic, in Conference on Uncertainty in Artificial Intelligence, 2010.PDF icon broecheler-uai10.pdf (399.54 KB)
M. Broecheler and Getoor, L., Probabilistic Similarity Logic, in International Workshop on Statistical Relational Learning (SRL'09), 2009.PDF icon broecheler-srl09.pdf (176.13 KB)
S. H. Bach, Huang, B., and Getoor, L., Probabilistic Soft Logic for Social Good, in KDD Workshop on Data Science for Social Good, 2014.PDF icon bach-dssg14.pdf (124.88 KB)
B. Huang, Kimmig, A., Getoor, L., and Golbeck, J., Probabilistic Soft Logic for Trust Analysis in Social Networks, in UAI Workshop on StaRAI , 2012.PDF icon huang-starai12.pdf (241.96 KB)
S. Kim, Kini, N., Pujara, J., Koh, E., and Getoor, L., Probabilistic Visitor Stitching on Cross-Device Web Logs, in International Conference on World Wide Web (WWW), 2017, pp. 1581–1589.PDF icon p1581-kimwww17.pdf (1.23 MB)
L. Getoor and Scheffer, T., Proceedings of the 28th International Conference on Machine Learning, in Proceedings of the 28th International Conference on Machine Learning, 2011.
L. Singh, Getoor, L., and Licamele, L., Pruning Social Networks Using Structural Properties and Descriptive Attributes, in IEEE International Conference on Data Mining (ICDM), 2005, pp. 773-776.PDF icon singh_icdm05.pdf (149.45 KB)
Q
I. Bhattacharya, Licamele, L., and Getoor, L., Query-Time Entity Resolution, in ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2006.PDF icon kdd06.pdf (183.45 KB)
G. Namata, London, B., Getoor, L., and Huang, B., Query-driven Active Surveying for Collective Classification, in ICML Workshop on MLG, 2012.PDF icon namata-mlg12.pdf (257.49 KB)
I. Bhattacharya and Getoor, L., Query-time Entity Resolution, Journal of Artificial Intelligence Research (JAIR), vol. 30, pp. 621–657, 2007.PDF icon bhattacharya07a.pdf (309.63 KB)
R
A. Grycner, Weikum, G., Pujara, J., Foulds, J., and Getoor, L., RELLY: Inferring Hypernym Relationships Between Relational Phrases, in Conference on Empirical Methods in Natural Language Processing, 2015.PDF icon agrycner-emnlp15.pdf (234.86 KB)
P. Sen, Deshpande, A., and Getoor, L., Read-Once Functions and Query Evaluation in Probabilistic Databases, in International Conference on Very Large Data Bases, 2010.PDF icon draft.pdf (322 KB)
J. Pujara, London, B., and Getoor, L., Reducing Label Cost by Combining Feature Labels and Crowdsourcing, in ICML Workshop on Combining Learning Strategies to Reduce Label Cost, 2011.PDF icon clsicml_pujara_london.pdf (253.29 KB)
M. Bilgic and Getoor, L., Reflect and Correct: A Misclassification Prediction Approach to Active Inference, ACM Transactions on Knowledge Discovery from Data, vol. 3, pp. 1–32, 2009.PDF icon bilgic-tkdd09.pdf (3.66 MB)
I. Bhattacharya, Licamele, L., and Getoor, L., Relational Clustering for Entity Resolution Queries, in ICML Workshop on Statistical Relational Learning (SRL), 2006.PDF icon bhattacharyaicml06-wkshp.pdf (195.79 KB)
I. Bhattacharya and Getoor, L., Relational Clustering for Multi-type Entity Resolution, in ACM SIGKDD Workshop on Multi Relational Data Mining (MRDM), 2005.PDF icon bhattacharyakdd05-whskp.pdf (259.82 KB)
C. Diehl, Namata, G. Mark, and Getoor, L., Relationship Identification for Social Network Discovery, in AAAI '07: Proceedings of the 22nd National Conference on Artificial Intelligence, 2007.PDF icon diehl-aaai07.pdf (139.6 KB)
P. Sen, Deshpande, A., and Getoor, L., Representing Tuple and Attribute Uncertainty in Probabilistic Databases, in Workshop on Data Mining of Uncertain Data (ICDM), 2007.PDF icon dune07.pdf (176.67 KB)
S. H. Bach, Huang, B., and Getoor, L., Rounding Guarantees for Message-Passing MAP Inference with Logical Dependencies, in NIPS Workshop on Discrete and Combinatorial Problems in Machine Learning (DISCML), 2014.PDF icon bach-discml14.pdf (254.9 KB)
S
D. Sridhar, Pujara, J., and Getoor, L., Scalable Probabilistic Causal Structure Discovery, in International Joint Conference on Artificial Intelligence (IJCAI), 2018.PDF icon sridhar-ijcai18.pdf (281.32 KB)
V. Embar, Sridhar, D., Farnadi, G., and Getoor, L., Scalable Structure Learning for Probabilistic Soft Logic, in IJCAI Workshop on Statistical Relational AI (StarAI), 2018.PDF icon embar-starai18.pdf (400.23 KB)
S. Bach, Broecheler, M., Getoor, L., and O'Leary, D., Scaling MPE Inference for Constrained Continuous Markov Random Fields with Consensus Optimization, in NeuRIPS, 2012.PDF icon bach-nips12.pdf (274.58 KB)
A. Lansky and Getoor, L., Scope and Abstraction: Two Criteria for Localized Planning, in Proceedings of the International Joint Conference on Arti cial Intelligence, 1995.
A. Lansky and Getoor, L., Scope and Abstraction: Two Criteria for Localized Planning, in Proceedings of the Workshop on Theory Reformulation and Abstraction, 1994.
L. Getoor, Koller, D., and Taskar, B., Selectivity estimation using probabilistic relational models, in Proceedings of ACM-SIGMOD 2001 International Conference on Management of Data, 2001.PDF icon sigmod01.pdf (471.72 KB)
L. Licamele and Getoor, L., Social Capital in Friendship-Event Networks, in IEEE International Conference on Data Mining (ICDM), 2006.
H. Bert, Stephen, B., Eric, N., Jay, P., and Getoor, L., Social Group Modeling with Probabilistic Soft Logic, in NeuRIPS Workshop on SNSMA, 2012.PDF icon huang-snsma12.pdf (1.02 MB)
G. Farnadi, Bach, S. H., Moens, M. - F., Getoor, L., and De Cock, M., Soft quantification in statistical relational learning, Machine Learning Journal, 2017.PDF icon farnadi-mlj17.pdf (1.24 MB)
T. Rekatsinas, Ghosh, S., Mekaru, S., Nsoesie, E., Brownstein, J., Getoor, L., and Ramakrishnan, N., SourceSeer: Forecasting Rare Disease Outbreaks Using Multiple Data Sources, in 2015 SIAM International Conference on Data Mining (SDM15), 2015.PDF icon rekatsinasSDM2015.pdf (303.08 KB)

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