Publications

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B. London, Huang, B., and Getoor, L., Stability and Generalization in Structured Prediction, , 2015.PDF icon london-stability15.pdf (532.16 KB)
B. London, Huang, B., and Getoor, L., Stability and Generalization in Structured Prediction, Journal of Machine Learning Research, vol. 17, 2016.PDF icon london-jmlr17.pdf (532.8 KB)
R. Islamaj, Getoor, L., W. Wilbur, J., and Mount, S., SplicePort - An interactive splice-site analysis tool, Nucleic Acids Research, 2007.PDF icon dogan-nar.pdf (1.34 MB)
J. Pujara, Augustine, E., and Getoor, L., Sparsity and Noise: Where Knowledge Graph Embeddings Fall Short, in Conference on Empirical Methods in Natural Language Processing (EMNLP), 2017.PDF icon pujara-emnlp17.pdf (677.74 KB)
T. Rekatsinas, Deshpande, A., Dong, L., Getoor, L., and Srivastava, D., SourceSight: Enabling Effective Source Selection, in SIGMOD, 2016.PDF icon rekatsinas-sigmod16.pdf (799.94 KB)
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)
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)
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)
L. Licamele and Getoor, L., Social Capital in Friendship-Event Networks, in IEEE International Conference on Data Mining (ICDM), 2006.
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)
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.
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)
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)
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)
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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)
T. Elsayed, Oard, D., and Namata, G. Mark, Resolving Personal Names in Email Using Context Expansion, in 46th Annual Meeting of the Association of Computational Linguistics, 2008, pp. 265–268.PDF icon elsayed-acl08.pdf (294.84 KB)
P. Kouki, Resolution, Recommendation, and Explanation in Richly Structured Social Networks, 2018.PDF icon kouki-dissertation.pdf (6.94 MB)
P. Sen, Representing and Querying Uncertain Data, University of Maryland, College Park, 2009.PDF icon thesis.pdf (1.12 MB)
P. Sen and Deshpande, A., Representing and Querying Correlated Tuples in Probabilistic Databases, in International Conference on Data Engineering, 2007.PDF icon icde07_final.pdf (309.63 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)
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)
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)
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)
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)
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)
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)
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)
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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)
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, 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)
T. Rekatsinas, Quality-Aware Data Source Management, University of Maryland, College Park, 2015.
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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)
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.
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)
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. 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)
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)
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, 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)
J. Pujara, Probabilistic Models for Scalable Knowledge Graph Construction, University of Maryland, College Park, 2016.PDF icon pujara-thesis15.pdf (1.06 MB)
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.
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)
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.
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)
E. Zheleva, Terzi, E., and Getoor, L., Privacy in Social Networks, vol. 4. Morgan & Claypool Publishers, 2012.
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)

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