Publications

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Bach, S. H., Huang, B., Boyd-Graber, J. & Getoor, L. Paired-Dual Learning for Fast Training of Latent Variable Hinge-Loss MRFs. International Conference on Machine Learning (ICML) (2015).PDF icon bach-icml15.pdf (356.46 KB)
Elsayed, T., Oard, D., Namata, G. Mark & Getoor, L. Personal Name Resolution in Email: A Heuristic Approach. (2008).PDF icon LAMP_150.pdf (397.61 KB)
Kouki, P., Schaffer, J., Pujara, J., Odonovan, J. & Getoor, L. Personalized Explanations for Hybrid Recommender Systems. IUI (2019).PDF icon kouki-iui19.pdf (3.34 MB)
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)
Sen, P., Deshpande, A. & 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)
Lansky, A. & Getoor, L. Practical Planning in COLLAGE. Proceedings of the AAAI Fall Symposium on Planning and Learning: On to Real Applications (1994).
Tomkins, S., Ramesh, A. & Getoor, L. Predicting Post-Test Performance from Online Student Behavior: A High School MOOC Case Study. EDM (2016).PDF icon tomkins-edm16.pdf (619.77 KB)
Licamele, L. & Getoor, L. Predicting Protein-Protein Interactions Using Relational Features. ICML Workshop on Statistical Network Analysis (2006).
Zheleva, E. & Getoor, L. Preserving the Privacy of Sensitive Relationships in Graph Data. Proceedings of the First SIGKDD International Workshop on Privacy, Security, and Trust in KDD (PinKDD 2007) 4890, 153-171 (Springer, 2008).
Zheleva, E. & Getoor, L. Preserving the Privacy of Sensitive Relationships in Graph Data. First ACM SIGKDD Workshop on Privacy, Security, and Trust in KDD (PinKDD 2007) (2007).PDF icon zheleva-pinkdd07.pdf (373.86 KB)
Zheleva, E., Terzi, E. & Getoor, L. Privacy in Social Networks. Synthesis Lectures on Data Mining and Knowledge Discovery 4, (Morgan & Claypool Publishers, 2012).
Zheleva, E. & Getoor, L. Privacy in Social Networks: A Survey. Social Network Data Analytics 1, 247–276 (Springer, 2011).PDF icon zheleva-book11.pdf (791.3 KB)
Plangprasopchok, A., Lerman, K. & Getoor, L. A Probabilistic Approach for Learning Folksonomies from Structured Data. Fourth ACM International Conference on Web Search and Data Mining (WSDM) (2011).
Sridhar, D. & Getoor, L. Probabilistic Inference for Causal Structure Discovery. UAI Workshop on Causation (2016).PDF icon sridhar-causation16.pdf (118.31 KB)
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).
Getoor, L., Segal, E., Taskar, B. & Koller, D. Probabilistic Models of Text and Link Structure for Hypertext Classification. IJCAI Workshop on Text Learning: Beyond Supervision (2001).PDF icon ijcai01-ws.pdf (127.03 KB)
Getoor, L., Friedman, N., Koller, D., Pfeffer, A. & Taskar, B. Probabilistic Relational Models. An Introduction to Statistical Relational Learning 1, 129--174 (MIT Press, 2007).PDF icon getoor-book07.pdf (648.15 KB)
Getoor, L., Friedman, N., Koller, D., Pfeffer, A. & Taskar, B. Probabilistic Relational Models. An Introduction to Statistical Relational Learning 1, 129--174 (MIT Press, 2007).PDF icon getoor-book07.pdf (648.15 KB)
Broecheler, M., Mihalkova, L. & Getoor, L. Probabilistic Similarity Logic. Conference on Uncertainty in Artificial Intelligence (2010).PDF icon broecheler-uai10.pdf (399.54 KB)
Broecheler, M. & Getoor, L. Probabilistic Similarity Logic. International Workshop on Statistical Relational Learning (SRL'09) (2009).PDF icon broecheler-srl09.pdf (176.13 KB)
Bach, S. H., Huang, B. & Getoor, L. Probabilistic Soft Logic for Social Good. KDD Workshop on Data Science for Social Good (2014).PDF icon bach-dssg14.pdf (124.88 KB)
Huang, B., Kimmig, A., Getoor, L. & Golbeck, J. Probabilistic Soft Logic for Trust Analysis in Social Networks. UAI Workshop on StaRAI (2012).PDF icon huang-starai12.pdf (241.96 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)
Getoor, L. & Scheffer, T. Proceedings of the 28th International Conference on Machine Learning. Proceedings of the 28th International Conference on Machine Learning (2011).
Singh, L., Getoor, L. & Licamele, L. Pruning Social Networks Using Structural Properties and Descriptive Attributes. IEEE International Conference on Data Mining (ICDM) 773-776 (2005).PDF icon singh_icdm05.pdf (149.45 KB)
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Bhattacharya, I., Licamele, L. & Getoor, L. Query-Time Entity Resolution. ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (2006).PDF icon kdd06.pdf (183.45 KB)
Namata, G., London, B., Getoor, L. & Huang, B. Query-driven Active Surveying for Collective Classification. ICML Workshop on MLG (2012).PDF icon namata-mlg12.pdf (257.49 KB)
Bhattacharya, I. & Getoor, L. Query-time Entity Resolution. Journal of Artificial Intelligence Research (JAIR) 30, 621–657 (2007).PDF icon bhattacharya07a.pdf (309.63 KB)
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Grycner, A., Weikum, G., Pujara, J., Foulds, J. & Getoor, L. RELLY: Inferring Hypernym Relationships Between Relational Phrases. Conference on Empirical Methods in Natural Language Processing (2015).PDF icon agrycner-emnlp15.pdf (234.86 KB)
Sen, P., Deshpande, A. & Getoor, L. Read-Once Functions and Query Evaluation in Probabilistic Databases. International Conference on Very Large Data Bases (2010).PDF icon draft.pdf (322 KB)
Pujara, J., London, B. & Getoor, L. Reducing Label Cost by Combining Feature Labels and Crowdsourcing. ICML Workshop on Combining Learning Strategies to Reduce Label Cost (2011).PDF icon clsicml_pujara_london.pdf (253.29 KB)
Bilgic, M. & Getoor, L. Reflect and Correct: A Misclassification Prediction Approach to Active Inference. ACM Transactions on Knowledge Discovery from Data 3, 1–32 (2009).PDF icon bilgic-tkdd09.pdf (3.66 MB)
Bhattacharya, I., Licamele, L. & Getoor, L. Relational Clustering for Entity Resolution Queries. ICML Workshop on Statistical Relational Learning (SRL) (2006).PDF icon bhattacharyaicml06-wkshp.pdf (195.79 KB)
Bhattacharya, I. & Getoor, L. Relational Clustering for Multi-type Entity Resolution. ACM SIGKDD Workshop on Multi Relational Data Mining (MRDM) (2005).PDF icon bhattacharyakdd05-whskp.pdf (259.82 KB)
Diehl, C., Namata, G. Mark & Getoor, L. Relationship Identification for Social Network Discovery. AAAI '07: Proceedings of the 22nd National Conference on Artificial Intelligence (2007).PDF icon diehl-aaai07.pdf (139.6 KB)
Sen, P., Deshpande, A. & Getoor, L. Representing Tuple and Attribute Uncertainty in Probabilistic Databases. Workshop on Data Mining of Uncertain Data (ICDM) (2007).PDF icon dune07.pdf (176.67 KB)
Bach, S. H., Huang, B. & Getoor, L. Rounding Guarantees for Message-Passing MAP Inference with Logical Dependencies. NIPS Workshop on Discrete and Combinatorial Problems in Machine Learning (DISCML) (2014).PDF icon bach-discml14.pdf (254.9 KB)
S
Sridhar, D., Pujara, J. & Getoor, L. Scalable Probabilistic Causal Structure Discovery. International Joint Conference on Artificial Intelligence (2018). at <https://bitbucket.org/linqs/causpsl/src/master/>PDF icon sridhar-ijcai18.pdf (281.32 KB)
Embar, V., Sridhar, D., Farnadi, G. & Getoor, L. Scalable Structure Learning for Probabilistic Soft Logic. Workshop on Statistical Relational AI (2018).PDF icon VEmbar-StarAI2018.pdf (400.23 KB)
Bach, S., Broecheler, M., Getoor, L. & O'Leary, D. Scaling MPE Inference for Constrained Continuous Markov Random Fields with Consensus Optimization. NeuRIPS (2012).PDF icon bach-nips12.pdf (274.58 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. & Getoor, L. Scope and Abstraction: Two Criteria for Localized Planning. Proceedings of the Workshop on Theory Reformulation and Abstraction (1994).
Getoor, L., Koller, D. & Taskar, B. Selectivity estimation using probabilistic relational models. Proceedings of ACM-SIGMOD 2001 International Conference on Management of Data (2001).PDF icon sigmod01.pdf (471.72 KB)
Licamele, L. & Getoor, L. Social Capital in Friendship-Event Networks. IEEE International Conference on Data Mining (ICDM) (2006).
Bert, H., Stephen, B., Eric, N., Jay, P. & Getoor, L. Social Group Modeling with Probabilistic Soft Logic. NeuRIPS Workshop on SNSMA (2012).PDF icon huang-snsma12.pdf (1.02 MB)
Tomkins, S., Getoor, L., Chen, Y. & Zhang, Y. A Socio-linguistic Model for Cyberbullying Detection. International Conference on Advances in Social Networks Analysis and Mining (ASONAM) (2018).PDF icon tomkins-asonam18.pdf (299.34 KB)
Farnadi, G., Bach, S. H., Moens, M. - F., Getoor, L. & De Cock, M. Soft quantification in statistical relational learning. Machine Learning Journal (2017).PDF icon farnadi-mlj17.pdf (1.24 MB)
Rekatsinas, T. et al. SourceSeer: Forecasting Rare Disease Outbreaks Using Multiple Data Sources. 2015 SIAM International Conference on Data Mining (SDM15) (SIAM, 2015).PDF icon rekatsinasSDM2015.pdf (303.08 KB)
Rekatsinas, T., Deshpande, A., Dong, L., Getoor, L. & Srivastava, D. SourceSight: Enabling Effective Source Selection. SIGMOD (2016).PDF icon rekatsinas-sigmod16.pdf (799.94 KB)

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